diff --git a/README.md b/README.md
index 382bccc..0af619a 100644
--- a/README.md
+++ b/README.md
@@ -66,6 +66,7 @@ For more examples, you may also find our [Blog](https://haystack.deepset.ai/blog
 | Evaluating RAG Pipelines with EvaluationHarness | <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag_eval_harness.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
 | Define & Run Tools | <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/tools_support.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
 | Agentic RAG with Llama 3.2 3B | <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/llama32_agentic_rag.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
+| Enhanced RAG with NVIDIA NIM Rankers | <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/enhanced_rag_with_nvidia_nim_rankers.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
 | Cohere for Multilingual QA (Haystack 1.x)| <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/cohere-for-multilingual-qa.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
 | GPT-4 and Weaviate for Custom Documentation QA (Haystack 1.x)| <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/gpt4-weaviate-custom-documentation-qa.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
 | Whisper Transcriber and Weaviate for YouTube video QA (Haystack 1.x)| <a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/whisper-and-weaviate-for-youtube-rag.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>|
diff --git a/index.toml b/index.toml
index 0ab71d8..214430c 100644
--- a/index.toml
+++ b/index.toml
@@ -266,4 +266,10 @@ notebook = "newsletter-agent.ipynb"
 new = true
 experimental = true
 topics = ["Function Calling", "Chat", "Agents"]
-discuss = "https://github.com/deepset-ai/haystack-experimental/discussions/98"
\ No newline at end of file
+discuss = "https://github.com/deepset-ai/haystack-experimental/discussions/98"
+
+[[cookbook]]
+title = "Enhanced RAG with NVIDIA NIM Rankers"
+notebook = "enhanced_rag_with_nvidia_nim_rankers.ipynb"
+new = true
+topics = ["RAG", "Advanced Retrieval"]
\ No newline at end of file
diff --git a/notebooks/enhanced_rag_with_nvidia_nim_rankers.ipynb b/notebooks/enhanced_rag_with_nvidia_nim_rankers.ipynb
new file mode 100644
index 0000000..d9e98ae
--- /dev/null
+++ b/notebooks/enhanced_rag_with_nvidia_nim_rankers.ipynb
@@ -0,0 +1,3341 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7_7WJMZ8jSLK"
+      },
+      "source": [
+        "# Enhanced RAG with NVIDIA NIM Rankers\n",
+        "by Bilge Yucel ([X](https://x.com/bilgeycl), [Linkedin](https://www.linkedin.com/in/bilge-yucel/))\n",
+        "\n",
+        "\n",
+        "**Ranking** refers to assigning a relevance score to each document based on how well it matches the query. Adding a ranker component to a RAG pipeline enhances both **recall** (retrieving relevant documents) and **precision** (selecting the most relevant ones). The ranker, typically using a fine-tuned **LLM**, reorders retrieved document chunks to ensure the most relevant ones appear at the top, making the retrieval process not only faster but also more accurate.\n",
+        "\n",
+        "By prioritizing the right documents, ranking increases the likelihood of providing the LLM with the best context, which improves the quality of generated responses.\n",
+        "\n",
+        "In this cookbook, we will build a pipeline with the [NvidiaRanker](https://docs.haystack.deepset.ai/docs/nvidiaranker) and compare the answers of basic RAG pipeline with the enhanced RAG pipeline with ranker."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1sVCsnz0-gVi"
+      },
+      "source": [
+        "## Installation\n",
+        "\n",
+        "Start by installing `nvidia-haystack` and `datasets` packages:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "collapsed": true,
+        "id": "TApYFisjWW-c",
+        "outputId": "33550a41-f72f-4acf-8269-3bf8d5016873"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Collecting nvidia-haystack\n",
+            "  Downloading nvidia_haystack-0.0.5-py3-none-any.whl.metadata (2.2 kB)\n",
+            "Collecting datasets\n",
+            "  Downloading datasets-3.0.2-py3-none-any.whl.metadata (20 kB)\n",
+            "Collecting haystack-ai (from nvidia-haystack)\n",
+            "  Downloading haystack_ai-2.6.1-py3-none-any.whl.metadata (13 kB)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from nvidia-haystack) (2.32.3)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.16.1)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.26.4)\n",
+            "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (16.1.0)\n",
+            "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n",
+            "  Downloading dill-0.3.8-py3-none-any.whl.metadata (10 kB)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.2.2)\n",
+            "Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.5)\n",
+            "Collecting xxhash (from datasets)\n",
+            "  Downloading xxhash-3.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (12 kB)\n",
+            "Collecting multiprocess<0.70.17 (from datasets)\n",
+            "  Downloading multiprocess-0.70.16-py310-none-any.whl.metadata (7.2 kB)\n",
+            "Requirement already satisfied: fsspec<=2024.9.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets) (2024.6.1)\n",
+            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.10.10)\n",
+            "Requirement already satisfied: huggingface-hub>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.24.7)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.1)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.2)\n",
+            "Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (2.4.3)\n",
+            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n",
+            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (24.2.0)\n",
+            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n",
+            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.1.0)\n",
+            "Requirement already satisfied: yarl<2.0,>=1.12.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.16.0)\n",
+            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.23.0->datasets) (4.12.2)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->nvidia-haystack) (3.4.0)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->nvidia-haystack) (3.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->nvidia-haystack) (2.2.3)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->nvidia-haystack) (2024.8.30)\n",
+            "Collecting haystack-experimental (from haystack-ai->nvidia-haystack)\n",
+            "  Downloading haystack_experimental-0.2.0-py3-none-any.whl.metadata (11 kB)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from haystack-ai->nvidia-haystack) (3.1.4)\n",
+            "Collecting lazy-imports (from haystack-ai->nvidia-haystack)\n",
+            "  Downloading lazy_imports-0.3.1-py3-none-any.whl.metadata (10 kB)\n",
+            "Requirement already satisfied: more-itertools in /usr/local/lib/python3.10/dist-packages (from haystack-ai->nvidia-haystack) (10.5.0)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from haystack-ai->nvidia-haystack) (3.4.2)\n",
+            "Collecting openai>=1.1.0 (from haystack-ai->nvidia-haystack)\n",
+            "  Downloading openai-1.52.2-py3-none-any.whl.metadata (24 kB)\n",
+            "Collecting posthog (from haystack-ai->nvidia-haystack)\n",
+            "  Downloading posthog-3.7.0-py2.py3-none-any.whl.metadata (2.0 kB)\n",
+            "Requirement already satisfied: python-dateutil in /usr/local/lib/python3.10/dist-packages (from haystack-ai->nvidia-haystack) (2.8.2)\n",
+            "Requirement already satisfied: tenacity!=8.4.0 in /usr/local/lib/python3.10/dist-packages (from haystack-ai->nvidia-haystack) (9.0.0)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.2)\n",
+            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai>=1.1.0->haystack-ai->nvidia-haystack) (3.7.1)\n",
+            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/lib/python3/dist-packages (from openai>=1.1.0->haystack-ai->nvidia-haystack) (1.7.0)\n",
+            "Collecting httpx<1,>=0.23.0 (from openai>=1.1.0->haystack-ai->nvidia-haystack)\n",
+            "  Downloading httpx-0.27.2-py3-none-any.whl.metadata (7.1 kB)\n",
+            "Collecting jiter<1,>=0.4.0 (from openai>=1.1.0->haystack-ai->nvidia-haystack)\n",
+            "  Downloading jiter-0.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (5.2 kB)\n",
+            "Requirement already satisfied: pydantic<3,>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from openai>=1.1.0->haystack-ai->nvidia-haystack) (2.9.2)\n",
+            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from openai>=1.1.0->haystack-ai->nvidia-haystack) (1.3.1)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil->haystack-ai->nvidia-haystack) (1.16.0)\n",
+            "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from yarl<2.0,>=1.12.0->aiohttp->datasets) (0.2.0)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->haystack-ai->nvidia-haystack) (3.0.2)\n",
+            "Collecting monotonic>=1.5 (from posthog->haystack-ai->nvidia-haystack)\n",
+            "  Downloading monotonic-1.6-py2.py3-none-any.whl.metadata (1.5 kB)\n",
+            "Collecting backoff>=1.10.0 (from posthog->haystack-ai->nvidia-haystack)\n",
+            "  Downloading backoff-2.2.1-py3-none-any.whl.metadata (14 kB)\n",
+            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->openai>=1.1.0->haystack-ai->nvidia-haystack) (1.2.2)\n",
+            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai>=1.1.0->haystack-ai->nvidia-haystack)\n",
+            "  Downloading httpcore-1.0.6-py3-none-any.whl.metadata (21 kB)\n",
+            "Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai>=1.1.0->haystack-ai->nvidia-haystack)\n",
+            "  Downloading h11-0.14.0-py3-none-any.whl.metadata (8.2 kB)\n",
+            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.9.0->openai>=1.1.0->haystack-ai->nvidia-haystack) (0.7.0)\n",
+            "Requirement already satisfied: pydantic-core==2.23.4 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.9.0->openai>=1.1.0->haystack-ai->nvidia-haystack) (2.23.4)\n",
+            "Downloading nvidia_haystack-0.0.5-py3-none-any.whl (21 kB)\n",
+            "Downloading datasets-3.0.2-py3-none-any.whl (472 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m472.7/472.7 kB\u001b[0m \u001b[31m9.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading multiprocess-0.70.16-py310-none-any.whl (134 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m9.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading haystack_ai-2.6.1-py3-none-any.whl (372 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m372.1/372.1 kB\u001b[0m \u001b[31m21.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading xxhash-3.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading openai-1.52.2-py3-none-any.whl (386 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m386.9/386.9 kB\u001b[0m \u001b[31m20.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading haystack_experimental-0.2.0-py3-none-any.whl (68 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m68.5/68.5 kB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading lazy_imports-0.3.1-py3-none-any.whl (12 kB)\n",
+            "Downloading posthog-3.7.0-py2.py3-none-any.whl (54 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.4/54.4 kB\u001b[0m \u001b[31m2.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading backoff-2.2.1-py3-none-any.whl (15 kB)\n",
+            "Downloading httpx-0.27.2-py3-none-any.whl (76 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.4/76.4 kB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading httpcore-1.0.6-py3-none-any.whl (78 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m78.0/78.0 kB\u001b[0m \u001b[31m4.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading jiter-0.6.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (325 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m325.2/325.2 kB\u001b[0m \u001b[31m18.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading monotonic-1.6-py2.py3-none-any.whl (8.2 kB)\n",
+            "Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m3.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: monotonic, xxhash, lazy-imports, jiter, h11, dill, backoff, posthog, multiprocess, httpcore, httpx, openai, datasets, haystack-experimental, haystack-ai, nvidia-haystack\n",
+            "Successfully installed backoff-2.2.1 datasets-3.0.2 dill-0.3.8 h11-0.14.0 haystack-ai-2.6.1 haystack-experimental-0.2.0 httpcore-1.0.6 httpx-0.27.2 jiter-0.6.1 lazy-imports-0.3.1 monotonic-1.6 multiprocess-0.70.16 nvidia-haystack-0.0.5 openai-1.52.2 posthog-3.7.0 xxhash-3.5.0\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install nvidia-haystack datasets"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "U_Yh0y9YH4VO"
+      },
+      "source": [
+        "## Dataset\n",
+        "\n",
+        "Install the [HotpotQA dataset](https://huggingface.co/datasets/hotpotqa/hotpot_qa) from Hugging Face:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 313,
+          "referenced_widgets": [
+            "ceaf9babbb164804822aedafc76859d0",
+            "b1fa835f1c0e41fa943d12a145feb306",
+            "d0d5fa80dc2e4afeb243b8e9e773b564",
+            "dffea9f5cfca40fcaee3c11c6f9ba386",
+            "925e94cc42d04d338aa41c8a905b9faf",
+            "8b586cf008f8492a86d3770f6e29c340",
+            "45b9e581154141d4aa6634a7e4db7172",
+            "61220bad11934e8eb2ee438c581bba58",
+            "5a57615e2166429da4e8b4654d8c9ce2",
+            "0a18f7930848428699edfcf040632527",
+            "7f846bc2293346a6969289cba0a19b50",
+            "e449e3334fea41a4b4b44425ce769ca0",
+            "01d39f717b8343ffbe90cd5167abe2d2",
+            "d3dee5ae50414e5f99e39f71798c2ad8",
+            "9eae47a5ebd94300a76b87e0ad7658b2",
+            "b374b263f45d490d9f745a143012d005",
+            "1b1ee95a4c0940308e1eda0b15922507",
+            "5563221219134f299bd2499fbd0f78bd",
+            "2aae515263fb41b988ee00b7535b0823",
+            "f983a139b8924adb93ba03ed61d8dbd3",
+            "0ca97b85f8954eb089fe6c5feb0ce1ad",
+            "56ba0c6b72cd45fea7d6a70a9dc1cd0e",
+            "135659c254dd4ef9908eba7fd4a8f869",
+            "3f0fda8751d641dfb996996238ca726e",
+            "625d19a64e3b4ec88905e579db8832f2",
+            "19e3651a63174826a5505deaed2a404c",
+            "b831a9017472466aa02ae866880bad0d",
+            "afdc35f58a0d4d1397538d2d7ea26e0c",
+            "d765e94d41554f7f9ab1802d50c9ae67",
+            "c83f4f1d85754194a257f13e9805d5bc",
+            "64a8ffc932344d3f947f57239edc5e63",
+            "3e22585362d140089093bf53751be94b",
+            "4096e236d3424cb29a4d1da5b5af65f2",
+            "78d44514004647d494d6d1ada94a0818",
+            "18eb1c9220634269a0fc94b4600ef980",
+            "bb867cd4dd2449e2b3ebfd06bc9e9624",
+            "5f760f95b30a4038a6ebf96cb1e24531",
+            "6c20cd089bad4483a5cc22be1ffb0414",
+            "f5af9025565b46218f634fbb1dbe7469",
+            "249e98b589264f00a81564cd39e7d653",
+            "9ce3a203bbd842ea975ff1cb1c845ec7",
+            "6738c8c67ccf46eb8a772ec45246eb33",
+            "47cff8ee61ae4007a8dd94048a10ee7f",
+            "5435d77b1e994cbeb24baf0d855677df",
+            "5b04064937664315914919f8aad03943",
+            "d25abb46556c44c588f72a9a6945a970",
+            "b796cf4bb964443880e12df6e0d74bc0",
+            "bcad5a00446d4d0ead41f1217b9e5e1c",
+            "29b2dfab67bf47bf985759e6f3903262",
+            "65dd2e8cb2f64a55a9f59fe442640005",
+            "f8d708df3fb14cec9c08c22a6fff5878",
+            "b0e775055c204169985d0e821e998bb2",
+            "6eaf383543de4a4e98fcb45a56f01750",
+            "c2e49e93cf964be6b95ceac4a59c7b78",
+            "18cc4e4d62024e8cae2996d2baa53946",
+            "3027dd90d2ad4a7092aa4fd8a00b817b",
+            "03a2bed5fd474f68b85ee12b59dc36c3",
+            "d2c1d7df1ca44286b55bcbc622b871be",
+            "de8f857b75004b7d9c6850fd872a6da7",
+            "a6f68d997f354508903c3114015766ba",
+            "fce1c30f19c74be89fead02ecb9c6305",
+            "573c17dedafe4c4da1bc8218fa55c3a2",
+            "d8cc0fd9d16e458d86d32c4f34d69247",
+            "91b451d80baa43c085732b5fc7a60753",
+            "a698aafd07dc4e92b7a7d7b8b6c392b4",
+            "54d0cdb187c94dc6a75fb459fe0a3562"
+          ]
+        },
+        "collapsed": true,
+        "id": "IvHoBvBoWjnf",
+        "outputId": "a9d8e19d-5ebb-407d-f3a8-debaf76268d9"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
+            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+            "You will be able to reuse this secret in all of your notebooks.\n",
+            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "ceaf9babbb164804822aedafc76859d0",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "README.md:   0%|          | 0.00/9.19k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "e449e3334fea41a4b4b44425ce769ca0",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "hotpot_qa.py:   0%|          | 0.00/6.42k [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "135659c254dd4ef9908eba7fd4a8f869",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading data:   0%|          | 0.00/566M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "78d44514004647d494d6d1ada94a0818",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Downloading data:   0%|          | 0.00/46.3M [00:00<?, ?B/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "5b04064937664315914919f8aad03943",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Generating train split:   0%|          | 0/90447 [00:00<?, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "3027dd90d2ad4a7092aa4fd8a00b817b",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Generating validation split:   0%|          | 0/7405 [00:00<?, ? examples/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "from datasets import load_dataset\n",
+        "\n",
+        "data = load_dataset('hotpotqa/hotpot_qa', 'distractor', trust_remote_code=True)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ebL45uOGKsZ_"
+      },
+      "source": [
+        "Let's check an entry to understand the data structure. In Hotpot QA, each entry includes a question, a ground-truth answer, context sentences and titles."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "xI52-uDWKXI2",
+        "outputId": "ebb5bc0a-8e4a-4844-8ea5-55bc896c715d"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'id': '5a8e3ea95542995a26add48d',\n",
+              " 'question': 'The director of the romantic comedy \"Big Stone Gap\" is based in what New York city?',\n",
+              " 'answer': 'Greenwich Village, New York City',\n",
+              " 'type': 'bridge',\n",
+              " 'level': 'hard',\n",
+              " 'supporting_facts': {'title': ['Big Stone Gap (film)', 'Adriana Trigiani'],\n",
+              "  'sent_id': [0, 0]},\n",
+              " 'context': {'title': ['Just Another Romantic Wrestling Comedy',\n",
+              "   'Kingston Morning',\n",
+              "   'Nola (film)',\n",
+              "   'Adriana Trigiani',\n",
+              "   'Great Eastern Conventions',\n",
+              "   'New York Society of Model Engineers',\n",
+              "   'Clinton, Minnesota',\n",
+              "   \"Hamish and Andy's Gap Year\",\n",
+              "   'I Love NY (2015 film)',\n",
+              "   'Big Stone Gap (film)'],\n",
+              "  'sentences': [['Just Another Romantic Wrestling Comedy is a 2006 film starring April Hunter and Joanie Laurer.',\n",
+              "    ' This Romantic comedy film was premiered at New Jersey and New York City on December 1, 2006 and was released on DVD in the United States and the United Kingdom on April 17, 2007.',\n",
+              "    ' After the film\\'s DVD release \"Just Another Romantic Wrestling Comedy\" won an \"Honorable Mention\" award at the New Jersey International Festival awards.',\n",
+              "    ' The release is being handled by \"Victory Multimedia\".'],\n",
+              "   [\"Kingston Morning is Dave Eggar's 4th solo release recorded in Brooklyn, New York; Kingston, Jamaica; and Big Stone Gap, Virginia; and released by Domo Records.\",\n",
+              "    ' \"Itsbynne Reel\" was nominated at the 53rd Grammy Awards for \"Best Instrumental Arrangement\".'],\n",
+              "   ['Nola is a 2003 American romantic comedy film written and directed by Alan Hruska.',\n",
+              "    ' It depicts the struggle of a young woman trying to survive in New York City while looking for her birth father.',\n",
+              "    ' It premiered in New York City on July 23, 2004.'],\n",
+              "   ['Adriana Trigiani is an Italian American best-selling author of sixteen books, television writer, film director, and entrepreneur based in Greenwich Village, New York City.',\n",
+              "    ' Trigiani has published a novel a year since 2000.'],\n",
+              "   ['Great Eastern Conventions, Inc. was an entertainment company which produced comic book conventions, most actively during the years 1987-1996.',\n",
+              "    \" In New York City, the Great Eastern shows filled the gap between the mid-1980s demise of the annual Comic Art Convention and Creation Conventions, and the establishment of promoter Michael Carbonaro's annual Big Apple Comic Con in 1996.\",\n",
+              "    ' From 1993–1995, Great Eastern hosted two New York City shows annually at the Jacob K. Javits Convention Center.',\n",
+              "    ' Great Eastern also ran shows in New Jersey, Pennsylvania, Massachusetts, Oregon, Minnesota, and Texas.'],\n",
+              "   ['The New York Society of Model Engineers (NYSME) was originally incorporated in 1926 in New York City.',\n",
+              "    ' There are published records that show the Society existed as early as 1905.',\n",
+              "    ' In its early years, the organization moved to and from various locations throughout Manhattan.',\n",
+              "    \" AT that time it was basically a gentlemen's club of members who were interested in all types of model building.\",\n",
+              "    ' In 1926 the Society was formalized and incorporated under the laws of the State of New York.',\n",
+              "    \" This was done so that the Society could obtain a permit to use a lake in New York City's Central Park for model motor boat races.\",\n",
+              "    ' It was also at this time that the Society began construction of its first Model Railroad \" The Union Connecting\".',\n",
+              "    ' Over the next twenty years, the Society moved from its original location to two other locations.',\n",
+              "    ' Each move doubling the size of the previous location and of course doubling the size of the model train layout.',\n",
+              "    ' During WW2 many Society members were called to service in the Armed Forces.',\n",
+              "    ' Regrettably, the largest of the layouts had to be dismantled.',\n",
+              "    ' The location of the layout in the basement of the Astor Building was requested for the war effort.',\n",
+              "    ' The dismantling was done with care, with salvaged usable materials going into scrap drives for the War effort.',\n",
+              "    ' As members returned after the War a new location was searched for.',\n",
+              "    ' This led to an invitation from the Lackawanna Railroad to move into their Passenger Terminal in Hoboken,NJ.',\n",
+              "    ' They had the space for what would become the largest model railroad in the world at that time.',\n",
+              "    ' The space?',\n",
+              "    ' Only the ornate waiting room for the recently discontinued ferry boats to 23rd Street in New York City.',\n",
+              "    ' Here the layout was built.',\n",
+              "    ' It was based on the Lackawanna Railroad from Hoboken to Scranton, Pa.',\n",
+              "    ' It was magnificent; from the scale model of the Hoboken Terminal to the soaring Delaware Water Gap.',\n",
+              "    ' During the early-1950s the organization moved to its current location in Carlstadt, New Jersey.'],\n",
+              "   ['Clinton is a city in Big Stone County, Minnesota, United States.',\n",
+              "    ' The city was named for New York Governor DeWitt Clinton.',\n",
+              "    ' The population was 449 at the 2010 census.'],\n",
+              "   [\"Hamish & Andy's Gap Year is a Logie Award winning comedy series following Hamish Blake and Andy Lee, a pair of Australian comedians, on their trips to various international locations.\",\n",
+              "    ' The first season saw the boys visiting America for ten episodes and broadcast their show weekly from New York City.',\n",
+              "    ' In its second season in 2012, the show was titled \"Hamish & Andy\\'s Euro Gap Year\" and seven episodes were broadcast from The Lord Stanley, a disused pub in East London, England.',\n",
+              "    ' The third season known as \"Hamish and Andy\\'s Gap Year Asia\" in 2013 was broadcast from a bar in Bangkok, Thailand, called \\'The Raintree\\'.'],\n",
+              "   ['I Love NY, also known as I Love New Year, is an Indian romantic comedy film directed by Radhika Rao and Vinay Sapru starring Sunny Deol and Kangana Ranaut in lead roles.',\n",
+              "    ' The film is produced by Bhushan Kumar and Krishan Kumar under the banner of Super Cassettes Industries Ltd.',\n",
+              "    ' The film was extensively shot in Mumbai, New York City and Bangkok.',\n",
+              "    ' The main plot was taken from the Russian romantic comedy \"The Irony of Fate\" (1976).',\n",
+              "    ' After numerous delays, the film released on 10 July 2015.'],\n",
+              "   ['Big Stone Gap is a 2014 American drama romantic comedy film written and directed by Adriana Trigiani and produced by Donna Gigliotti for Altar Identity Studios, a subsidiary of Media Society.',\n",
+              "    \" Based on Trigiani's 2000 best-selling novel of the same name, the story is set in the actual Virginia town of Big Stone Gap circa 1970s.\",\n",
+              "    ' The film had its world premiere at the Virginia Film Festival on November 6, 2014.']]}}"
+            ]
+          },
+          "execution_count": 3,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "data[\"validation\"][4]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "PfXBIvokJwwq"
+      },
+      "source": [
+        "We'll now convert the Hotpot QA dataset entries into Haystack Documents. We'll merge the sentences to into meaningful chunks and use the title as meta info in our Haystack Document object."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 121,
+          "referenced_widgets": [
+            "fda86af527c140d0a9c666e9d4ca4b52",
+            "9f1bc7b795064f0dafbaa50bc3ac967f",
+            "7de2db53efd54890a9a95eff1387d675",
+            "15b84e82b83b416fa9a15c68bb4f2313",
+            "7dfaffe124c743d2bd18f20c0733f5c7",
+            "ee0f0ddc219f42019f5d564de8c3191c",
+            "e09dc212d3684002aa851306d270e884",
+            "28c64510ddaa4ee895c58bc377b83d72",
+            "7bcb425966c7475d91b9f290bf98bc6b",
+            "cf2eb3edd90349d4b601ac7ad4279830",
+            "8baf1dae012d4fddacc1ccd9ab18500b"
+          ]
+        },
+        "id": "9fqcx1kVWiys",
+        "outputId": "0cf1e975-e3d1-426d-c19a-ab71be548a99"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.10/dist-packages/haystack/core/errors.py:34: DeprecationWarning: PipelineMaxLoops is deprecated and will be remove in version '2.7.0'; use PipelineMaxComponentRuns instead.\n",
+            "  warnings.warn(\n",
+            "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "fda86af527c140d0a9c666e9d4ca4b52",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "0it [00:00, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "from haystack.dataclasses.document import Document\n",
+        "\n",
+        "def convert_hotpot_dataset(data):\n",
+        "    doc_chunks = []\n",
+        "\n",
+        "    for item in data:\n",
+        "        # Collect the relevant content\n",
+        "        context_dict = {item['context'][\"title\"][i]: item['context'][\"sentences\"][i] for i in range(len(item['context'][\"title\"]))}\n",
+        "\n",
+        "        # Convert to Haystack Documents\n",
+        "        for k, v in context_dict.items():\n",
+        "            content = ''.join(v).strip()\n",
+        "            doc_chunks.append(Document(content=content, meta={\"title\":k}))\n",
+        "\n",
+        "    return doc_chunks\n",
+        "\n",
+        "documents = convert_hotpot_dataset(data[\"validation\"])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8MRjK2M6enAu",
+        "outputId": "702b5c2d-be3e-4ab4-c99e-0ad7abe26b9a"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Document(id=52837c52309de1827a1ca76200774451a415376a784eba418d851d0fd59196cc, content: 'Ed Wood is a 1994 American biographical period comedy-drama film directed and produced by Tim Burton...', meta: {'title': 'Ed Wood (film)'})\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(documents[0])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "7kDJdN4TLa3H"
+      },
+      "source": [
+        "## Indexing Documents\n",
+        "\n",
+        "To create a pipeline to index our documents, we need an NVIDIA NIM api key. You can get 1k credits for free after [signing up](https://org.ngc.nvidia.com/setup/personal-keys) for NVIDIA's platform. Once you have you your api key, set it as `\"NVIDIA_API_KEY\"` environment variable."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "PAo_uL_aca98"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "\n",
+        "os.environ[\"NVIDIA_API_KEY\"] = \"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\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OyqBofNhM_ia"
+      },
+      "source": [
+        "Next, create a pipeline and index your documents. For embeddings, we'll use the[`nvidia/nv-embedqa-e5-v5`](https://docs.api.nvidia.com/nim/reference/nvidia-nv-embedqa-e5-v5) model through [NvidiaDocumentEmbedder](https://docs.haystack.deepset.ai/docs/nvidiadocumentembedder)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KvWdsE09cDT0",
+        "outputId": "06e5be26-1835-4baa-e4a9-8153ad9f8e90"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Calculating embeddings: 100%|██████████| 16/16 [00:10<00:00,  1.53it/s]\n",
+            "WARNING:haystack.document_stores.in_memory.document_store:ID 'c2655213e385f148113573dac0552f2df726c4406ce5a32d9518ea092e2de914' already exists\n",
+            "WARNING:haystack.document_stores.in_memory.document_store:ID 'a67d430a1525668a4111b5068f4ab679e8529b0769822ddd04f791952442a0b8' already exists\n",
+            "WARNING:haystack.document_stores.in_memory.document_store:ID '6ea5ef5b6c3bf3a5c7e5eba4df906b6a4f98aea31cd1daa93f212d62b3181f78' already exists\n",
+            "WARNING:haystack.document_stores.in_memory.document_store:ID 'd02279eb622a4955476a60f27e731f957c472ef22d3393d9576be83ade7d6c48' already exists\n",
+            "WARNING:haystack.document_stores.in_memory.document_store:ID '16b4cbc532ae2fa19e074d23cbb12104ffa4a6de07fe979815449de05f1d71aa' already exists\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "505\n"
+          ]
+        }
+      ],
+      "source": [
+        "from haystack.document_stores.in_memory import InMemoryDocumentStore\n",
+        "from haystack.dataclasses.document import Document\n",
+        "from haystack.components.writers import DocumentWriter\n",
+        "from haystack_integrations.components.embedders.nvidia import NvidiaDocumentEmbedder\n",
+        "from haystack import Pipeline\n",
+        "from haystack.document_stores.types import DuplicatePolicy\n",
+        "from haystack.components.preprocessors import DocumentSplitter\n",
+        "\n",
+        "document_store = InMemoryDocumentStore()\n",
+        "embedder = NvidiaDocumentEmbedder(model=\"nvidia/nv-embedqa-e5-v5\",\n",
+        "                                  api_url=\"https://integrate.api.nvidia.com/v1\")\n",
+        "\n",
+        "indexing_pipeline = Pipeline()\n",
+        "indexing_pipeline.add_component(instance=DocumentSplitter(split_length=350, split_overlap=50), name=\"splitter\")\n",
+        "indexing_pipeline.add_component(instance=embedder, name=\"embedder\")\n",
+        "indexing_pipeline.add_component(instance=DocumentWriter(document_store=document_store, policy=DuplicatePolicy.SKIP), name=\"writer\")\n",
+        "indexing_pipeline.connect(\"splitter\", \"embedder\")\n",
+        "indexing_pipeline.connect(\"embedder.documents\", \"writer.documents\")\n",
+        "\n",
+        "indexing_pipeline.run({\"splitter\":{\"documents\": documents[:500]}}) # We dont need to index all documents\n",
+        "\n",
+        "print(document_store.count_documents())"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "imlq0e2_SmCo"
+      },
+      "source": [
+        "## Enhanced RAG with Ranker\n",
+        "Let's now create a RAG pipeline with Ranker. For retrieval, we'll initialize the [NvidiaTextEmbedder](https://docs.haystack.deepset.ai/docs/nvidiatextembedder) and the [NvidiaRanker](https://docs.haystack.deepset.ai/docs/nvidiaranker) with the `nvidia/nv-rerankqa-mistral-4b-v3` model. We'll set the `top_k` value of retriever to 30 and of ranker to 5. Thus, we'll retrieve 30 docs but only pass the 5 most relevant documents as context to the LLM.\n",
+        "\n",
+        "For generation, we'll initialize [NvidiaGenerator](https://docs.haystack.deepset.ai/docs/nvidiagenerator) with the `meta/llama3-70b-instruct model`."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "GR6KHoceUqyF",
+        "outputId": "2a91c7b7-01d4-419a-f2d6-51f6119c88bc"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<haystack.core.pipeline.pipeline.Pipeline object at 0x7c0d9504f4f0>\n",
+              "🚅 Components\n",
+              "  - embedder: NvidiaTextEmbedder\n",
+              "  - retriever: InMemoryEmbeddingRetriever\n",
+              "  - ranker: NvidiaRanker\n",
+              "  - prompt_builder: PromptBuilder\n",
+              "  - generator: NvidiaGenerator\n",
+              "🛤️ Connections\n",
+              "  - embedder.embedding -> retriever.query_embedding (List[float])\n",
+              "  - retriever.documents -> ranker.documents (List[Document])\n",
+              "  - ranker.documents -> prompt_builder.documents (List[Document])\n",
+              "  - prompt_builder.prompt -> generator.prompt (str)"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from haystack import Pipeline\n",
+        "from haystack.utils.auth import Secret\n",
+        "from haystack.components.builders import PromptBuilder\n",
+        "from haystack_integrations.components.embedders.nvidia import NvidiaTextEmbedder\n",
+        "from haystack_integrations.components.generators.nvidia import NvidiaGenerator\n",
+        "from haystack_integrations.components.rankers.nvidia import NvidiaRanker\n",
+        "from haystack.components.retrievers import InMemoryEmbeddingRetriever\n",
+        "\n",
+        "embedder = NvidiaTextEmbedder(model=\"nvidia/nv-embedqa-e5-v5\",\n",
+        "                              api_url=\"https://integrate.api.nvidia.com/v1\")\n",
+        "\n",
+        "retriever = InMemoryEmbeddingRetriever(document_store=document_store, top_k=30)\n",
+        "ranker = NvidiaRanker(\n",
+        "    model=\"nvidia/nv-rerankqa-mistral-4b-v3\",\n",
+        "    top_k=5\n",
+        ")\n",
+        "\n",
+        "prompt = \"\"\"Answer the question given the context.\n",
+        "Question: {{ query }}\n",
+        "Context:\n",
+        "{% for document in documents %}\n",
+        "    {{ document.content }}\n",
+        "{% endfor %}\n",
+        "Answer:\n",
+        "\"\"\"\n",
+        "prompt_builder = PromptBuilder(template=prompt)\n",
+        "\n",
+        "generator = NvidiaGenerator(\n",
+        "    model=\"meta/llama3-70b-instruct\",\n",
+        "    model_arguments={\n",
+        "        \"max_tokens\": 1024\n",
+        "    }\n",
+        ")\n",
+        "\n",
+        "enhanced_rag = Pipeline()\n",
+        "enhanced_rag.add_component(\"embedder\", embedder)\n",
+        "enhanced_rag.add_component(\"retriever\", retriever)\n",
+        "enhanced_rag.add_component(\"ranker\", ranker)\n",
+        "enhanced_rag.add_component(\"prompt_builder\", prompt_builder)\n",
+        "enhanced_rag.add_component(\"generator\", generator)\n",
+        "\n",
+        "enhanced_rag.connect(\"embedder.embedding\", \"retriever.query_embedding\")\n",
+        "enhanced_rag.connect(\"retriever\", \"ranker\")\n",
+        "enhanced_rag.connect(\"ranker.documents\", \"prompt_builder.documents\")\n",
+        "enhanced_rag.connect(\"prompt_builder\", \"generator\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Xg4h8gtJfXUC"
+      },
+      "source": [
+        "Let's run the pipeline with some questions and compare the answers:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "eRrV_CvfWMki",
+        "outputId": "96a833f8-5f00-45a9-acce-678569b4cfaf"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'embedder': {'meta': {'usage': {'prompt_tokens': 23, 'total_tokens': 23}}},\n",
+              " 'generator': {'replies': [\"The director of the romantic comedy 'Big Stone Gap', Adriana Trigiani, is based in Greenwich Village, New York City.\"],\n",
+              "  'meta': [{'role': 'assistant',\n",
+              "    'usage': {'prompt_tokens': 380,\n",
+              "     'total_tokens': 408,\n",
+              "     'completion_tokens': 28},\n",
+              "    'finish_reason': 'stop'}]}}"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "question = \"Are the Laleli Mosque and Esma Sultan Mansion located in the same neighborhood?\" # answer is \"no\"\n",
+        "question = \"The director of the romantic comedy 'Big Stone Gap' is based in what New York city?\" # answer is \"Greenwich Village, New York City\"\n",
+        "\n",
+        "enhanced_rag.run({\n",
+        "    \"embedder\": {\"text\": question},\n",
+        "    \"ranker\": {\"query\": question},\n",
+        "    \"prompt_builder\": {\"query\": question}\n",
+        "})"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "t1K54b6Nfg85"
+      },
+      "source": [
+        "## Basic RAG Pipeline\n",
+        "\n",
+        "For comparison, let's define a basic pipeline (without a ranker) and see the result for the same questions."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "zRinctrniZPp",
+        "outputId": "cb30bb6b-37b2-4c87-8720-adfb479ec8c7"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<haystack.core.pipeline.pipeline.Pipeline object at 0x7c0d98944610>\n",
+              "🚅 Components\n",
+              "  - embedder: NvidiaTextEmbedder\n",
+              "  - retriever: InMemoryEmbeddingRetriever\n",
+              "  - prompt_builder: PromptBuilder\n",
+              "  - generator: NvidiaGenerator\n",
+              "🛤️ Connections\n",
+              "  - embedder.embedding -> retriever.query_embedding (List[float])\n",
+              "  - retriever.documents -> prompt_builder.documents (List[Document])\n",
+              "  - prompt_builder.prompt -> generator.prompt (str)"
+            ]
+          },
+          "execution_count": 14,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from haystack import Pipeline\n",
+        "from haystack.utils.auth import Secret\n",
+        "from haystack.components.builders import PromptBuilder\n",
+        "from haystack_integrations.components.embedders.nvidia import NvidiaTextEmbedder\n",
+        "from haystack_integrations.components.generators.nvidia import NvidiaGenerator\n",
+        "from haystack.components.retrievers import InMemoryEmbeddingRetriever\n",
+        "\n",
+        "embedder = NvidiaTextEmbedder(model=\"nvidia/nv-embedqa-e5-v5\",\n",
+        "                              api_url=\"https://integrate.api.nvidia.com/v1\")\n",
+        "\n",
+        "retriever = InMemoryEmbeddingRetriever(document_store=document_store, top_k=5)\n",
+        "\n",
+        "prompt = \"\"\"Answer the question given the context.\n",
+        "Question: {{ query }}\n",
+        "Context:\n",
+        "{% for document in documents %}\n",
+        "    {{ document.content }}\n",
+        "{% endfor %}\n",
+        "Answer:\n",
+        "\"\"\"\n",
+        "prompt_builder = PromptBuilder(template=prompt)\n",
+        "\n",
+        "generator = NvidiaGenerator(\n",
+        "    model=\"meta/llama3-70b-instruct\",\n",
+        "    model_arguments={\n",
+        "        \"max_tokens\": 1024\n",
+        "    }\n",
+        ")\n",
+        "\n",
+        "rag = Pipeline()\n",
+        "rag.add_component(\"embedder\", embedder)\n",
+        "rag.add_component(\"retriever\", retriever)\n",
+        "rag.add_component(\"prompt_builder\", prompt_builder)\n",
+        "rag.add_component(\"generator\", generator)\n",
+        "\n",
+        "rag.connect(\"embedder.embedding\", \"retriever.query_embedding\")\n",
+        "rag.connect(\"retriever\", \"prompt_builder.documents\")\n",
+        "rag.connect(\"prompt_builder\", \"generator\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "9MFzoBjCiL_K",
+        "outputId": "868018df-e1e2-4a27-a24b-3abef04bf671"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'embedder': {'meta': {'usage': {'prompt_tokens': 23, 'total_tokens': 23}}},\n",
+              " 'generator': {'replies': ['The answer is Brooklyn.'],\n",
+              "  'meta': [{'role': 'assistant',\n",
+              "    'usage': {'prompt_tokens': 473,\n",
+              "     'total_tokens': 479,\n",
+              "     'completion_tokens': 6},\n",
+              "    'finish_reason': 'stop'}]}}"
+            ]
+          },
+          "execution_count": 15,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "question = \"Are the Laleli Mosque and Esma Sultan Mansion located in the same neighborhood?\" # answer is \"no\"\n",
+        "question = \"The director of the romantic comedy 'Big Stone Gap' is based in what New York city?\" # answer is \"Greenwich Village, New York City\"\n",
+        "\n",
+        "rag.run({\n",
+        "    \"embedder\": {\"text\": question},\n",
+        "    \"prompt_builder\": {\"query\": question}\n",
+        "})"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "MYa_cQpqf9f1"
+      },
+      "source": [
+        "## Conclusion\n",
+        "\n",
+        "This recipe compares we compare two RAG pipelines: a basic RAG pipeline and an enhanced version that includes an `NvidiaRanker` with the `nvidia/nv-rerankqa-mistral-4b-v3`. While both use a context length of 5 documents, the enhanced RAG pipeline, thanks to the ranking model, provides more relevant documents for the LLM, leading to improved accuracy in the answer.\n",
+        "\n",
+        "For a detailed evaluation, read the full [blog post](https://haystack.deepset.ai/blog/rag-with-nvidia-nim-ranker)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "9Kc3K-6cjH7w"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "01d39f717b8343ffbe90cd5167abe2d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1b1ee95a4c0940308e1eda0b15922507",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5563221219134f299bd2499fbd0f78bd",
+            "value": "hotpot_qa.py: 100%"
+          }
+        },
+        "03a2bed5fd474f68b85ee12b59dc36c3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fce1c30f19c74be89fead02ecb9c6305",
+            "placeholder": "​",
+            "style": "IPY_MODEL_573c17dedafe4c4da1bc8218fa55c3a2",
+            "value": "Generating validation split: 100%"
+          }
+        },
+        "0a18f7930848428699edfcf040632527": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0ca97b85f8954eb089fe6c5feb0ce1ad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "135659c254dd4ef9908eba7fd4a8f869": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3f0fda8751d641dfb996996238ca726e",
+              "IPY_MODEL_625d19a64e3b4ec88905e579db8832f2",
+              "IPY_MODEL_19e3651a63174826a5505deaed2a404c"
+            ],
+            "layout": "IPY_MODEL_b831a9017472466aa02ae866880bad0d"
+          }
+        },
+        "15b84e82b83b416fa9a15c68bb4f2313": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cf2eb3edd90349d4b601ac7ad4279830",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8baf1dae012d4fddacc1ccd9ab18500b",
+            "value": " 0/0 [00:00&lt;?, ?it/s]"
+          }
+        },
+        "18cc4e4d62024e8cae2996d2baa53946": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "18eb1c9220634269a0fc94b4600ef980": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f5af9025565b46218f634fbb1dbe7469",
+            "placeholder": "​",
+            "style": "IPY_MODEL_249e98b589264f00a81564cd39e7d653",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "19e3651a63174826a5505deaed2a404c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3e22585362d140089093bf53751be94b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4096e236d3424cb29a4d1da5b5af65f2",
+            "value": " 566M/566M [00:38&lt;00:00, 12.3MB/s]"
+          }
+        },
+        "1b1ee95a4c0940308e1eda0b15922507": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "249e98b589264f00a81564cd39e7d653": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "28c64510ddaa4ee895c58bc377b83d72": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": "20px"
+          }
+        },
+        "29b2dfab67bf47bf985759e6f3903262": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2aae515263fb41b988ee00b7535b0823": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3027dd90d2ad4a7092aa4fd8a00b817b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_03a2bed5fd474f68b85ee12b59dc36c3",
+              "IPY_MODEL_d2c1d7df1ca44286b55bcbc622b871be",
+              "IPY_MODEL_de8f857b75004b7d9c6850fd872a6da7"
+            ],
+            "layout": "IPY_MODEL_a6f68d997f354508903c3114015766ba"
+          }
+        },
+        "3e22585362d140089093bf53751be94b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3f0fda8751d641dfb996996238ca726e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_afdc35f58a0d4d1397538d2d7ea26e0c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d765e94d41554f7f9ab1802d50c9ae67",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "4096e236d3424cb29a4d1da5b5af65f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "45b9e581154141d4aa6634a7e4db7172": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "47cff8ee61ae4007a8dd94048a10ee7f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5435d77b1e994cbeb24baf0d855677df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "54d0cdb187c94dc6a75fb459fe0a3562": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5563221219134f299bd2499fbd0f78bd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "56ba0c6b72cd45fea7d6a70a9dc1cd0e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "573c17dedafe4c4da1bc8218fa55c3a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5a57615e2166429da4e8b4654d8c9ce2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "5b04064937664315914919f8aad03943": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d25abb46556c44c588f72a9a6945a970",
+              "IPY_MODEL_b796cf4bb964443880e12df6e0d74bc0",
+              "IPY_MODEL_bcad5a00446d4d0ead41f1217b9e5e1c"
+            ],
+            "layout": "IPY_MODEL_29b2dfab67bf47bf985759e6f3903262"
+          }
+        },
+        "5f760f95b30a4038a6ebf96cb1e24531": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_47cff8ee61ae4007a8dd94048a10ee7f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5435d77b1e994cbeb24baf0d855677df",
+            "value": " 46.3M/46.3M [00:03&lt;00:00, 11.6MB/s]"
+          }
+        },
+        "61220bad11934e8eb2ee438c581bba58": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "625d19a64e3b4ec88905e579db8832f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c83f4f1d85754194a257f13e9805d5bc",
+            "max": 566426227,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_64a8ffc932344d3f947f57239edc5e63",
+            "value": 566426227
+          }
+        },
+        "64a8ffc932344d3f947f57239edc5e63": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "65dd2e8cb2f64a55a9f59fe442640005": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6738c8c67ccf46eb8a772ec45246eb33": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6c20cd089bad4483a5cc22be1ffb0414": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6eaf383543de4a4e98fcb45a56f01750": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "78d44514004647d494d6d1ada94a0818": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_18eb1c9220634269a0fc94b4600ef980",
+              "IPY_MODEL_bb867cd4dd2449e2b3ebfd06bc9e9624",
+              "IPY_MODEL_5f760f95b30a4038a6ebf96cb1e24531"
+            ],
+            "layout": "IPY_MODEL_6c20cd089bad4483a5cc22be1ffb0414"
+          }
+        },
+        "7bcb425966c7475d91b9f290bf98bc6b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7de2db53efd54890a9a95eff1387d675": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_28c64510ddaa4ee895c58bc377b83d72",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7bcb425966c7475d91b9f290bf98bc6b",
+            "value": 0
+          }
+        },
+        "7dfaffe124c743d2bd18f20c0733f5c7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7f846bc2293346a6969289cba0a19b50": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8b586cf008f8492a86d3770f6e29c340": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8baf1dae012d4fddacc1ccd9ab18500b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "91b451d80baa43c085732b5fc7a60753": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "925e94cc42d04d338aa41c8a905b9faf": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9ce3a203bbd842ea975ff1cb1c845ec7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9eae47a5ebd94300a76b87e0ad7658b2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0ca97b85f8954eb089fe6c5feb0ce1ad",
+            "placeholder": "​",
+            "style": "IPY_MODEL_56ba0c6b72cd45fea7d6a70a9dc1cd0e",
+            "value": " 6.42k/6.42k [00:00&lt;00:00, 111kB/s]"
+          }
+        },
+        "9f1bc7b795064f0dafbaa50bc3ac967f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ee0f0ddc219f42019f5d564de8c3191c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e09dc212d3684002aa851306d270e884",
+            "value": ""
+          }
+        },
+        "a698aafd07dc4e92b7a7d7b8b6c392b4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a6f68d997f354508903c3114015766ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "afdc35f58a0d4d1397538d2d7ea26e0c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b0e775055c204169985d0e821e998bb2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b1fa835f1c0e41fa943d12a145feb306": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8b586cf008f8492a86d3770f6e29c340",
+            "placeholder": "​",
+            "style": "IPY_MODEL_45b9e581154141d4aa6634a7e4db7172",
+            "value": "README.md: 100%"
+          }
+        },
+        "b374b263f45d490d9f745a143012d005": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b796cf4bb964443880e12df6e0d74bc0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b0e775055c204169985d0e821e998bb2",
+            "max": 90447,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6eaf383543de4a4e98fcb45a56f01750",
+            "value": 90447
+          }
+        },
+        "b831a9017472466aa02ae866880bad0d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bb867cd4dd2449e2b3ebfd06bc9e9624": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9ce3a203bbd842ea975ff1cb1c845ec7",
+            "max": 46320117,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6738c8c67ccf46eb8a772ec45246eb33",
+            "value": 46320117
+          }
+        },
+        "bcad5a00446d4d0ead41f1217b9e5e1c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c2e49e93cf964be6b95ceac4a59c7b78",
+            "placeholder": "​",
+            "style": "IPY_MODEL_18cc4e4d62024e8cae2996d2baa53946",
+            "value": " 90447/90447 [00:41&lt;00:00, 2605.00 examples/s]"
+          }
+        },
+        "c2e49e93cf964be6b95ceac4a59c7b78": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c83f4f1d85754194a257f13e9805d5bc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ceaf9babbb164804822aedafc76859d0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b1fa835f1c0e41fa943d12a145feb306",
+              "IPY_MODEL_d0d5fa80dc2e4afeb243b8e9e773b564",
+              "IPY_MODEL_dffea9f5cfca40fcaee3c11c6f9ba386"
+            ],
+            "layout": "IPY_MODEL_925e94cc42d04d338aa41c8a905b9faf"
+          }
+        },
+        "cf2eb3edd90349d4b601ac7ad4279830": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d0d5fa80dc2e4afeb243b8e9e773b564": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_61220bad11934e8eb2ee438c581bba58",
+            "max": 9193,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_5a57615e2166429da4e8b4654d8c9ce2",
+            "value": 9193
+          }
+        },
+        "d25abb46556c44c588f72a9a6945a970": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_65dd2e8cb2f64a55a9f59fe442640005",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f8d708df3fb14cec9c08c22a6fff5878",
+            "value": "Generating train split: 100%"
+          }
+        },
+        "d2c1d7df1ca44286b55bcbc622b871be": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d8cc0fd9d16e458d86d32c4f34d69247",
+            "max": 7405,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_91b451d80baa43c085732b5fc7a60753",
+            "value": 7405
+          }
+        },
+        "d3dee5ae50414e5f99e39f71798c2ad8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2aae515263fb41b988ee00b7535b0823",
+            "max": 6422,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f983a139b8924adb93ba03ed61d8dbd3",
+            "value": 6422
+          }
+        },
+        "d765e94d41554f7f9ab1802d50c9ae67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d8cc0fd9d16e458d86d32c4f34d69247": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "de8f857b75004b7d9c6850fd872a6da7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a698aafd07dc4e92b7a7d7b8b6c392b4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_54d0cdb187c94dc6a75fb459fe0a3562",
+            "value": " 7405/7405 [00:03&lt;00:00, 2418.69 examples/s]"
+          }
+        },
+        "dffea9f5cfca40fcaee3c11c6f9ba386": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0a18f7930848428699edfcf040632527",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7f846bc2293346a6969289cba0a19b50",
+            "value": " 9.19k/9.19k [00:00&lt;00:00, 550kB/s]"
+          }
+        },
+        "e09dc212d3684002aa851306d270e884": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e449e3334fea41a4b4b44425ce769ca0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_01d39f717b8343ffbe90cd5167abe2d2",
+              "IPY_MODEL_d3dee5ae50414e5f99e39f71798c2ad8",
+              "IPY_MODEL_9eae47a5ebd94300a76b87e0ad7658b2"
+            ],
+            "layout": "IPY_MODEL_b374b263f45d490d9f745a143012d005"
+          }
+        },
+        "ee0f0ddc219f42019f5d564de8c3191c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f5af9025565b46218f634fbb1dbe7469": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f8d708df3fb14cec9c08c22a6fff5878": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f983a139b8924adb93ba03ed61d8dbd3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fce1c30f19c74be89fead02ecb9c6305": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fda86af527c140d0a9c666e9d4ca4b52": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9f1bc7b795064f0dafbaa50bc3ac967f",
+              "IPY_MODEL_7de2db53efd54890a9a95eff1387d675",
+              "IPY_MODEL_15b84e82b83b416fa9a15c68bb4f2313"
+            ],
+            "layout": "IPY_MODEL_7dfaffe124c743d2bd18f20c0733f5c7"
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}