---
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.