From 07f62e3b9c51a069ba5751b7b2efa698ff377ef7 Mon Sep 17 00:00:00 2001 From: Daniel Lok Date: Fri, 6 Sep 2024 15:35:01 +0800 Subject: [PATCH] Add a community notebook for fine-tuning with QLoRA, PEFT, and MLflow (#33319) add notebook for finetuning with mlflow Signed-off-by: Daniel Lok --- docs/source/en/community.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/source/en/community.md b/docs/source/en/community.md index 7890cb22ca58..ac3050d9dd77 100644 --- a/docs/source/en/community.md +++ b/docs/source/en/community.md @@ -67,3 +67,4 @@ This page regroups resources around 🤗 Transformers developed by the community | [Detect objects in an image with DETR](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/DETR/DETR_minimal_example_(with_DetrFeatureExtractor).ipynb) | How to use a trained *DetrForObjectDetection* model to detect objects in an image and visualize attention | [Niels Rogge](https://github.com/NielsRogge) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/DETR/DETR_minimal_example_(with_DetrFeatureExtractor).ipynb) | | [Fine-tune DETR on a custom object detection dataset](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/DETR/Fine_tuning_DetrForObjectDetection_on_custom_dataset_(balloon).ipynb) | How to fine-tune *DetrForObjectDetection* on a custom object detection dataset | [Niels Rogge](https://github.com/NielsRogge) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/DETR/Fine_tuning_DetrForObjectDetection_on_custom_dataset_(balloon).ipynb) | | [Finetune T5 for Named Entity Recognition](https://github.com/ToluClassics/Notebooks/blob/main/T5_Ner_Finetuning.ipynb) | How to fine-tune *T5* on a Named Entity Recognition Task | [Ogundepo Odunayo](https://github.com/ToluClassics) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1obr78FY_cBmWY5ODViCmzdY6O1KB65Vc?usp=sharing) | +| [Fine-Tuning Open-Source LLM using QLoRA with MLflow and PEFT](https://github.com/mlflow/mlflow/blob/master/docs/source/llms/transformers/tutorials/fine-tuning/transformers-peft.ipynb) | How to use [QLoRA](https://github.com/artidoro/qlora) and [PEFT](https://huggingface.co/docs/peft/en/index) to fine-tune an LLM in a memory-efficient way, while using [MLflow](https://mlflow.org/docs/latest/llms/transformers/index.html) to manage experiment tracking | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mlflow/mlflow/blob/master/docs/source/llms/transformers/tutorials/fine-tuning/transformers-peft.ipynb) |