diff --git a/README.rst b/README.rst index cc31074d531de..89ed934527d8a 100644 --- a/README.rst +++ b/README.rst @@ -129,7 +129,10 @@ In addition to supervised fine-tuning (SFT), NeMo also supports the latest param LLMs and MMs Deployment and Optimization ######################################## -NeMo LLMs and MMs can be deployed and optimized with `NVIDIA Inference Microservices (Early Access) `_, in short, NIMs. +NeMo LLMs and MMs can be deployed and optimized with `NVIDIA NeMo Microservices `_. + +Speech AI +######### NeMo ASR and TTS models can be optimized for inference and deployed for production use cases with `NVIDIA Riva `_. @@ -198,7 +201,7 @@ The NeMo Framework can be installed in a variety of ways, depending on your need * Conda / Pip - Refer to `Conda <#conda>`_ and `Pip <#pip>`_ for installation instructions. - * This is the recommended method for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) domains. + * This is the recommended method for ASR and TTS domains. * When using a Nvidia PyTorch container as the base, this is the recommended method for all domains. * Docker Containers - Refer to `Docker containers <#docker-containers>`_ for installation instructions. @@ -207,7 +210,7 @@ The NeMo Framework can be installed in a variety of ways, depending on your need * LLMs and MMs Dependencies - Refer to `LLMs and MMs Dependencies <#install-llms-and-mms-dependencies>`_ for installation instructions. -**Important: We strongly recommended that you start with a base NVIDIA PyTorch container: `nvcr.io/nvidia/pytorch:24.02-py3`** +**Important: We strongly recommended that you start with a base NVIDIA PyTorch container: nvcr.io/nvidia/pytorch:24.02-py3.** Conda ^^^^^^ @@ -439,11 +442,7 @@ Transformer Engine requires PyTorch to be built with at least CUDA 11.8. Megatron Core ^^^^^^^^^^^^^ -Megatron Core is required for LLM and MM domains. - -Megatron Core is a library for scaling large Transformer-based models. NeMo LLMs and MMs leverage Megatron Core for model parallelism, - -transformer architectures, and optimized PyTorch datasets. +Megatron Core is required for LLM and MM domains. Megatron Core is a library for scaling large Transformer-based models. NeMo LLMs and MMs leverage Megatron Core for model parallelism, transformer architectures, and optimized PyTorch datasets. To install Megatron Core, run the following code: @@ -464,18 +463,13 @@ NeMo Text Processing, specifically Inverse Text Normalization, is now a separate Docker Containers ----------------- -NeMo containers are launched concurrently with NeMo version updates. For example, the release of NeMo ``r1.23.0`` comes with the container ``nemo:24.01.speech``. The latest containers are: - -* NeMo LLM and MM container - `nvcr.io/nvidia/nemo:24.03.framework` -* NeMo Speech container - `nvcr.io/nvidia/nemo:24.01.speech` - -You can find additional information about released containers on the `NeMo releases page `_. +NeMo containers are launched concurrently with NeMo version updates. NeMo Framework now supports LLMs, MMs, ASR, and TTS in a single consolidated Docker container. You can find additional information about released containers on the `NeMo releases page `_. To use a pre-built container, run the following code: .. code-block:: bash - docker pull nvcr.io/nvidia/nemo:24.01.speech + docker pull nvcr.io/nvidia/nemo:24.05 To build a nemo container with Dockerfile from a branch, run the following code: @@ -519,4 +513,4 @@ Licenses * `NeMo GitHub Apache 2.0 license `__ -* NeMo is licensed under the `NVIDIA AI PRODUCT AGREEMENT `__. By pulling and using the container, you accept the terms and conditions of this license. \ No newline at end of file +* NeMo is licensed under the `NVIDIA AI PRODUCT AGREEMENT `__. By pulling and using the container, you accept the terms and conditions of this license.