From 6073b85b66e0cf3cb542ad7ab6b755aa72ce4255 Mon Sep 17 00:00:00 2001
From: Maxime Labonne <81252890+mlabonne@users.noreply.github.com>
Date: Sat, 13 Jan 2024 12:49:37 +0000
Subject: [PATCH] Update README.md
---
README.md | 11 +++++------
1 file changed, 5 insertions(+), 6 deletions(-)
diff --git a/README.md b/README.md
index 881e196..d2e0943 100644
--- a/README.md
+++ b/README.md
@@ -26,15 +26,15 @@ A list of notebooks and articles related to large language models.
|---------------------------------------|-------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|
| Fine-tune Llama 2 in Google Colab | Step-by-step guide to fine-tune your first Llama 2 model. | [Article](https://mlabonne.github.io/blog/posts/Fine_Tune_Your_Own_Llama_2_Model_in_a_Colab_Notebook.html) |
|
| Fine-tune LLMs with 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) | W.I.P. |
-| Fine-tune a Mistral-7b model with DPO | Boost the performance of supervised fine-tuned models with DPO. | [Article](https://medium.com/towards-data-science/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac) |
|
+| Fine-tune Mistral-7b with DPO | Boost the performance of supervised fine-tuned models with DPO. | [Article](https://medium.com/towards-data-science/fine-tune-a-mistral-7b-model-with-direct-preference-optimization-708042745aac) |
|
### Quantization
| Notebook | Description | Article | Notebook |
|---------------------------------------|-------------------------------------------------------------------------|---------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------|
-| 1. Introduction to Weight Quantization | Large language model optimization using 8-bit quantization. | [Article](https://mlabonne.github.io/blog/posts/Introduction_to_Weight_Quantization.html) |
|
-| 2. 4-bit LLM Quantization using GPTQ | Quantize your own open-source LLMs to run them on consumer hardware. | [Article](https://mlabonne.github.io/blog/4bit_quantization/) |
|
-| 3. Quantize Llama 2 models 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) |
|
+| 1. Introduction to Quantization | Large language model optimization using 8-bit quantization. | [Article](https://mlabonne.github.io/blog/posts/Introduction_to_Weight_Quantization.html) |
|
+| 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/) |
|
+| 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) |
|
| 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) |
|
### Other
@@ -44,8 +44,7 @@ A list of notebooks and articles related to large language models.
| Decoding Strategies in Large Language Models | A guide to text generation from beam search to nucleus sampling | [Article](https://mlabonne.github.io/blog/posts/2022-06-07-Decoding_strategies.html) |
|
| Visualizing GPT-2's Loss Landscape | 3D plot of the loss landscape based on weight perturbations. | [Tweet](https://twitter.com/maximelabonne/status/1667618081844219904) |
|
| Improve ChatGPT with Knowledge Graphs | Augment ChatGPT's answers with knowledge graphs. | [Article](https://mlabonne.github.io/blog/posts/Article_Improve_ChatGPT_with_Knowledge_Graphs.html) |
|
-| Merge Large Language Models with mergekit | Create your own models easily, no GPU required! | [Article](https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54
-) |
|
+| Merge LLMs with mergekit | Create your own models easily, no GPU required! | [Article](https://towardsdatascience.com/merge-large-language-models-with-mergekit-2118fb392b54) |
|
## 🧩 LLM Fundamentals