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add llama 3.1 fine-tuning with unsloth

Maxime Labonne пре 1 година
родитељ
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e472998403
1 измењених фајлова са 8 додато и 7 уклоњено
  1. 8 7
      README.md

+ 8 - 7
README.md

@@ -39,20 +39,21 @@ A list of notebooks and articles related to large language models.
 
 | Notebook | Description | Article | Notebook |
 |---------------------------------------|-------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Fine-tune Llama 2 with SFT | Step-by-step guide to supervised fine-tune Llama 2 in Google Colab. | [Article](https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html) | <a href="https://colab.research.google.com/drive/1PEQyJO1-f6j0S_XJ8DV50NkpzasXkrzd?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| Fine-tune Llama 2 with QLoRA | Step-by-step guide to supervised fine-tune Llama 2 in Google Colab. | [Article](https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html) | <a href="https://colab.research.google.com/drive/1PEQyJO1-f6j0S_XJ8DV50NkpzasXkrzd?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
 | Fine-tune CodeLlama using Axolotl | End-to-end guide to the state-of-the-art tool for fine-tuning. | [Article](https://mlabonne.github.io/blog/posts/A_Beginners_Guide_to_LLM_Finetuning.html) | <a href="https://colab.research.google.com/drive/1Xu0BrCB7IShwSWKVcfAfhehwjDrDMH5m?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
-| Fine-tune Mistral-7b with SFT | Supervised fine-tune Mistral-7b in a free-tier Google Colab with TRL. | - | <a href="https://colab.research.google.com/drive/1o_w0KastmEJNVwT5GoqMCciH-18ca5WS?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| Fine-tune Mistral-7b with QLoRA | Supervised fine-tune Mistral-7b in a free-tier Google Colab with TRL. |  | <a href="https://colab.research.google.com/drive/1o_w0KastmEJNVwT5GoqMCciH-18ca5WS?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
 | Fine-tune Mistral-7b with DPO | Boost the performance of supervised fine-tuned models with DPO. | [Article](https://mlabonne.github.io/blog/posts/Fine_tune_Mistral_7b_with_DPO.html) | <a href="https://colab.research.google.com/drive/15iFBr1xWgztXvhrj5I9fBv20c7CFOPBE?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
 | Fine-tune Llama 3 with ORPO | Cheaper and faster fine-tuning in a single stage with ORPO. | [Article](https://mlabonne.github.io/blog/posts/2024-04-19_Fine_tune_Llama_3_with_ORPO.html) | <a href="https://colab.research.google.com/drive/1eHNWg9gnaXErdAa8_mcvjMupbSS6rDvi"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| Fine-tune Llama 3.1 with Unsloth | Ultra-efficient supervised fine-tuning in Google Colab. | [Article](https://mlabonne.github.io/blog/posts/2024-07-29_Finetune_Llama31.html) | <a href="https://colab.research.google.com/drive/164cg_O7SV7G8kZr_JXqLd6VC7pd86-1Z?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
 
 ### Quantization
 
 | Notebook | Description | Article | Notebook |
 |---------------------------------------|-------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|
-| 1. Introduction to Quantization | Large language model optimization using 8-bit quantization. | [Article](https://mlabonne.github.io/blog/posts/Introduction_to_Weight_Quantization.html) | <a href="https://colab.research.google.com/drive/1DPr4mUQ92Cc-xf4GgAaB6dFcFnWIvqYi?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
-| 2. 4-bit Quantization using GPTQ | Quantize your own open-source LLMs to run them on consumer hardware. | [Article](https://mlabonne.github.io/blog/4bit_quantization/) | <a href="https://colab.research.google.com/drive/1lSvVDaRgqQp_mWK_jC9gydz6_-y6Aq4A?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
-| 3. Quantization with GGUF and llama.cpp | Quantize Llama 2 models with llama.cpp and upload GGUF versions to the HF Hub. | [Article](https://mlabonne.github.io/blog/posts/Quantize_Llama_2_models_using_ggml.html) | <a href="https://colab.research.google.com/drive/1pL8k7m04mgE5jo2NrjGi8atB0j_37aDD?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
-| 4. ExLlamaV2: The Fastest Library to Run LLMs | Quantize and run EXL2 models and upload them to the HF Hub. | [Article](https://mlabonne.github.io/blog/posts/ExLlamaV2_The_Fastest_Library_to_Run%C2%A0LLMs.html) | <a href="https://colab.research.google.com/drive/1yrq4XBlxiA0fALtMoT2dwiACVc77PHou?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| Introduction to Quantization | Large language model optimization using 8-bit quantization. | [Article](https://mlabonne.github.io/blog/posts/Introduction_to_Weight_Quantization.html) | <a href="https://colab.research.google.com/drive/1DPr4mUQ92Cc-xf4GgAaB6dFcFnWIvqYi?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| 4-bit Quantization using GPTQ | Quantize your own open-source LLMs to run them on consumer hardware. | [Article](https://mlabonne.github.io/blog/4bit_quantization/) | <a href="https://colab.research.google.com/drive/1lSvVDaRgqQp_mWK_jC9gydz6_-y6Aq4A?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| Quantization with GGUF and llama.cpp | Quantize Llama 2 models with llama.cpp and upload GGUF versions to the HF Hub. | [Article](https://mlabonne.github.io/blog/posts/Quantize_Llama_2_models_using_ggml.html) | <a href="https://colab.research.google.com/drive/1pL8k7m04mgE5jo2NrjGi8atB0j_37aDD?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
+| ExLlamaV2: The Fastest Library to Run LLMs | Quantize and run EXL2 models and upload them to the HF Hub. | [Article](https://mlabonne.github.io/blog/posts/ExLlamaV2_The_Fastest_Library_to_Run%C2%A0LLMs.html) | <a href="https://colab.research.google.com/drive/1yrq4XBlxiA0fALtMoT2dwiACVc77PHou?usp=sharing"><img src="img/colab.svg" alt="Open In Colab"></a> |
 
 ### Other
 
@@ -66,7 +67,7 @@ A list of notebooks and articles related to large language models.
 
 ## 🧩 LLM Fundamentals
 
-This section introduces essential knowledge about mathematics, Python, and neural networks. You might not want to start here, but refer to it as needed.
+This section introduces essential knowledge about mathematics, Python, and neural networks. You might not want to start here but refer to it as needed.
 
 <details>
 <summary>Toggle section</summary>