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
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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