Zero to LitGPT (#1165)

Co-authored-by: Carlos Mocholí <[email protected]>

README.md

@@ -35,13 +35,12 @@
 
 ✅  [Quantization](tutorials/quantize.md): 4-bit floats, 8-bit integers, and double quantization.
 
-✅  [Exporting](https://github.com/Lightning-AI/litgpt/blob/wip/tutorials/convert_lit_models.md) to other popular model weight formats.
+✅  [Exporting](tutorials/convert_lit_models.md) to other popular model weight formats.
 
 ✅  Many popular datasets for [pretraining](tutorials/pretrain_tinyllama.md) and [finetuning](tutorials/prepare_dataset.md), and [support for custom datasets](tutorials/prepare_dataset.md#preparing-custom-datasets-for-instruction-finetuning).
 
 ✅  Readable and easy-to-modify code to experiment with the latest research ideas.
 
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@@ -59,8 +58,6 @@ The following [Lightning Studio](https://lightning.ai/lightning-ai/studios) temp
 
 
 
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@@ -107,6 +104,14 @@ For more information, refer to the [download](tutorials/download_model_weights.m
 
 
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+> [!NOTE]
+> We recommend starting with the **[Zero to Pretraining, Finetuning, and Using LLMs with LitGPT](https://chat.openai.com/c/tutorial/0_to_litgpt.md)** if you are looking to get started with using LitGPT.
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 ## Finetuning and pretraining
 
 LitGPT supports [pretraining](tutorials/pretrain_tinyllama.md) and [finetuning](tutorials/finetune.md) to optimize models on excisting or custom datasets. Below is an example showing how to finetune a model with LoRA:
@@ -324,6 +329,12 @@ If you have general questions about building with LitGPT, please [join our Disco
 
 ## Tutorials, how-to guides, and docs
 
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+> [!NOTE]
+> We recommend starting with the **[Zero to Pretraining, Finetuning, and Using LLMs with LitGPT](https://chat.openai.com/c/tutorial/0_to_litgpt.md)** if you are looking to get started with using LitGPT.
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+Tutorials and in-depth feature documentation can be found below:
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 -  Finetuning, incl. LoRA, QLoRA, and Adapters ([tutorials/finetune.md](tutorials/finetune.md))
 -  Pretraining ([tutorials/pretrain_tinyllama.md](tutorials/pretrain_tinyllama.md))
 -  Model evaluation ([tutorials/evaluation.md](tutorials/evaluation.md))