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Model: ik-ram28/MedMistralInstruct-CPT-SFT-7B
Source: Original Platform

README.md

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+---
+library_name: transformers
+tags:
+- medical
+license: apache-2.0
+language:
+- fr
+- en
+base_model:
+- ik-ram28/MedMistralInstruct-CPT-7B
+- mistralai/Mistral-7B-Instruct-v0.1
+---
+
+
+## MedMistralInstruct-CPT-SFT-7B
+
+### Model Description
+
+MedMistralInstruct-CPT-SFT-7B is a French medical language model based on Mistral-7B-Instruct-v0.1, adapted through Continual Pre-Training followed by Supervised Fine-Tuning. 
+
+### Model Details
+
+- **Model Type**: Causal Language Model
+- **Base Model**: Mistral-7B-Instruct-v0.1
+- **Language**: French
+- **Domain**: Medical/Healthcare
+- **Parameters**: 7 billion
+- **License**: Apache 2.0
+
+### Training Details
+
+**Continual Pre-Training (CPT)**
+- **Dataset**: NACHOS corpus (7.4 GB French medical texts)
+- **Training Duration**: 2.8 epochs
+- **Hardware**: 32 NVIDIA A100 80GB GPUs
+- **Training Time**: ~40 hours
+
+**Supervised Fine-Tuning (SFT)**
+- **Dataset**: 30K French medical question-answer pairs
+- **Method**: DoRA (Weight-Decomposed Low-Rank Adaptation)
+- **Training Duration**: 10 epochs
+- **Hardware**: 1 NVIDIA H100 80GB GPU
+- **Training Time**: ~42 hours
+
+
+### Computational Requirements
+- **Carbon Emissions**: 33.96 kgCO2e (CPT+SFT)
+- **Training Time**: 82 hours total (CPT+SFT)
+
+
+
+### Ethical Considerations
+- **Medical Accuracy**: For research and educational purposes only
+- **Professional Oversight**: Requires verification by qualified medical professionals
+- **Bias Awareness**: May contain biases from training data
+- **Privacy**: Do not input private health information
+
+### Citation
+```bibtex
+
+```
+
+### Contact
+For questions about these models, please contact: ikram.belmadani@lis-lab.fr