æLtorio
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README.md
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![Stage](https://img.shields.io/badge/stage-early%20development-yellow)![License](https://img.shields.io/badge/license-Apache%202.0-blue)![Contributors Welcome](https://img.shields.io/badge/contributors-welcome-brightgreen)[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
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## A Fine-tuned Radiology-focused Model based on Hugging Face's Idefics3 Model
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This repository contains a fine-tuned version of the Hugging Face [Idefics3-8B-Llama3](https://huggingface.co/HuggingFaceM4/Idefics3-8B-Llama3) model, built on top of the Meta Llama 3.1 8B architecture. Our model, `IDEFICS3_ROCO`, has been fine-tuned on the [Radiology Objects in Context (ROCO)](https://huggingface.co/datasets/eltorio/ROCO-radiology) dataset, a large-scale medical and multimodal imaging collection.
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* **Base Model:** Idefics3-8B-Llama3
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* **Fine-tuning Dataset:** Radiology Objects in Context (ROCO)
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* **License:** Apache-2.0
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* **Current Status:** Fine-tuning process is
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### Training Progress Status
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* Current checkpoint:
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* Estimated remaining GPU time:
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* Hardware requirements: T4 GPU with >16GB VRAM
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* Last update: november,
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### Fine-tuning Code
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2. **Getting Started**
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* Fork the repository
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* Resume from checkpoint
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* Follow instructions in [ROCO-idefics3.ipynb](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
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3. **Contact**
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### Docker Image
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A AI training docker image is available for this model. The image and includes all necessary dependencies to run the fine-tuning process.
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```bash
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```
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The Dockerfile is available in the [IDEFICS_ROCO repository](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/Dockerfile).
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### Acknowledgments
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This work was made possible by the [Hugging Face Transformers](https://huggingface.co/) library and the [ROCO-radiology dataset](https://huggingface.co/datasets/eltorio/ROCO-radiology).
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![Stage](https://img.shields.io/badge/stage-early%20development-yellow)![License](https://img.shields.io/badge/license-Apache%202.0-blue)![Contributors Welcome](https://img.shields.io/badge/contributors-welcome-brightgreen)[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
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## Star the project
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**If you appreciate my work, please consider giving it a star! 🤩**
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**I'm also looking for donations of free GPU time to complete the fine-tuning process.**
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**Please contact me if you can help! 🙏**
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## A Fine-tuned Radiology-focused Model based on Hugging Face's Idefics3 Model
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This repository contains a fine-tuned version of the Hugging Face [Idefics3-8B-Llama3](https://huggingface.co/HuggingFaceM4/Idefics3-8B-Llama3) model, built on top of the Meta Llama 3.1 8B architecture. Our model, `IDEFICS3_ROCO`, has been fine-tuned on the [Radiology Objects in Context (ROCO)](https://huggingface.co/datasets/eltorio/ROCO-radiology) dataset, a large-scale medical and multimodal imaging collection.
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* **Base Model:** Idefics3-8B-Llama3
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* **Fine-tuning Dataset:** Radiology Objects in Context (ROCO)
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* **License:** Apache-2.0
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* **Current Status:** Fine-tuning process is finished. Contributions to complete the fine-tuning / vallidation / test processes are welcome!
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### Training Progress Status
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* Current checkpoint: 12267 (100% completed)
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* Estimated remaining GPU time: 0 hours
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* Hardware requirements: T4 GPU with >16GB VRAM
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* Last update: november, 12th 2024
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### Fine-tuning Code
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2. **Getting Started**
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* Fork the repository
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* Resume from checkpoint 12267
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* Follow instructions in [ROCO-idefics3.ipynb](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/#fileId=https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
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3. **Contact**
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### Docker Image
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A AI training docker image is available for this model. The image and includes all necessary dependencies to run the fine-tuning process.
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You need to set the `HF_TOKEN` environment variable to your Hugging Face API token.
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You also need to have NVidia Docker container runtime installed.
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Finnaly, you need to run the container with GPU support with `--gpus all` option.
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The image is available on Docker Hub:
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```bash
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export HF_TOKEN=hf_some_token
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docker run --gpus all --user=42420:42420 -e HF_TOKEN=$HF_TOKEN -it sctg/roco-idefics3:latest bash -i /start.sh $HF_TOKEN
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```
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The Dockerfile is available in the [IDEFICS_ROCO repository](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/Dockerfile).
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### Acknowledgments
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This work was made possible by the [Hugging Face Transformers](https://huggingface.co/) library and the [ROCO-radiology dataset](https://huggingface.co/datasets/eltorio/ROCO-radiology).
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