Add MiniMedra 0.6b fine-tuned medical model with LFS

.gitattributes

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README.md

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+---
+library_name: transformers
+tags:
+- medical
+- healthcare
+- fine-tuned
+- gemma
+license: apache-2.0
+base_model: microsoft/DialoGPT-small
+model_type: gemma
+---
+
+# MiniMedra 0.6b
+
+MiniMedra 0.6b is a fine-tuned medical language model based on Gemma 0.6b architecture. This model has been specifically trained for medical and healthcare-related tasks.
+
+## Model Details
+
+- **Base Model**: Gemma 0.6b
+- **Fine-tuning**: LoRA (Low-Rank Adaptation)
+- **Domain**: Medical/Healthcare
+- **Parameters**: ~0.6 billion
+- **Format**: SafeTensors
+
+## Training
+
+This model was fine-tuned using Axolotl with LoRA adapters on medical datasets. The training focused on improving the model's understanding and generation capabilities for medical content.
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("drwlf/MiniMedra-0.6b")
+model = AutoModelForCausalLM.from_pretrained("drwlf/MiniMedra-0.6b")
+
+# Example usage
+input_text = "What are the symptoms of diabetes?"
+inputs = tokenizer.encode(input_text, return_tensors="pt")
+outputs = model.generate(inputs, max_length=100, temperature=0.7)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+## License
+
+Apache 2.0
+
+## Disclaimer
+
+This model is for research and educational purposes only. It should not be used as a substitute for professional medical advice, diagnosis, or treatment. Always consult with qualified healthcare professionals for medical concerns.
+

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