Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- eltorio/ROCO-radiology
+language:
+- en
+- fr
+base_model:
+- HuggingFaceM4/Idefics3-8B-Llama3
+---
+
+# IDEFICS3_ROCO
+
+![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)
+
+## A Fine-tuned Radiology-focused Model based on Hugging Face's Idefics3 Model
+
+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 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.
+
+### Model Information
+
+* **Base Model:** Idefics3-8B-Llama3
+* **Fine-tuning Dataset:** Radiology Objects in Context (ROCO)
+* **License:** Apache-2.0
+* **Current Status:** Fine-tuning process is currently halted at checkpoint 640 (out of 24,000) due to limitations with Colab Free T4 GPU unit. Contributions to complete the fine-tuning process are welcome!
+
+### Training Progress Status
+
+* Current checkpoint: 620-640/24000 (~2.7% completed)
+* Estimated remaining GPU time: ~57 hours
+* Hardware requirements: T4 GPU with >16GB VRAM
+* Last update: november, 7th 2021
+
+### Fine-tuning Code
+
+The fine-tuning code is available as a Jupyter Notebook in the [ROCO-radiology dataset repository](https://huggingface.co/datasets/eltorio/ROCO-radiology) on Hugging Face:
+
+* [ROCO-idefics3.ipynb](https://huggingface.co/eltorio/IDEFICS3_ROCO/blob/main/ROCO-idefics3.ipynb)
+
+The [Junyper Notebook](https://colab.research.google.com/#fileId=https%3A//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) contains the code to fine-tune the Idefics3-8B-Llama3 model on the ROCO dataset. The fine-tuning process is currently halted at checkpoint 640 (out of 24,000) due to limitations with Colab Free T4 GPU unit. Contributions to complete the fine-tuning process are welcome!
+
+### Contributions Welcome
+
+If you have the resources to complete the fine-tuning process, we would appreciate your contribution. Please fork this repository, finish the fine-tuning process, and submit a pull request with your updates.
+
+### Citation
+
+If you use this model in your work, please cite the original Idefics3 model and our fine-tuned model:
+
+* [Idefics3-8B-Llama3](https://huggingface.co/HuggingFaceM4/Idefics3-8B-Llama3)
+* [IDEFICS3_ROCO](https://huggingface.co/eltorio/IDEFICS3_ROCO)
+
+### Contribution Guide
+
+1. **Technical Requirements**
+   * Access to powerful GPU (T4, V100, A100 or equivalent)
+   * Python environment with PyTorch
+   * Disk space: ~50GB
+
+2. **Getting Started**
+   * Fork the repository
+   * Resume from checkpoint 640
+   * 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)
+
+3. **Contact**
+   * For questions: [link to issues/discussions]
+
+### Acknowledgments
+
+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).