transformers safetensors mistral text-generation biology medical QA healthcare conversational en dataset:medalpaca/medical_meadow_medqa license:mit autotrain_compatible text-generation-inference 4-bit bitsandbytes region:us
---
datasets:
- medalpaca/medical_meadow_medqa
language:
- en
library_name: transformers
license: mit
tags:
- biology
- medical
- QA
- healthcare
inference: false
---
# Galen
Galen is fine-tuned from [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2), using [medical quesion answering dataset](https://huggingface.co/datasets/medalpaca/medical_meadow_medqa)
### Galen's view about future of medicine and AI:
![alt text](1.png "Galen's view about future of medicine and AI")
# Get Started
Install "accelerate" to use CUDA GPU
```bash
pip install accelerate
```
```py
from transformers import AutoTokenizer, pipeline
```
```py
tokenizer = AutoTokenizer.from_pretrained('ahmed-ai/galen')
model_pipeline = pipeline(task="text-generation", model='ahmed-ai/galen', tokenizer=tokenizer, max_length=256, temperature=0.5, top_p=0.6)
```
```py
result = model_pipeline('What is squamous cell carcinoma')
#print the generated text
print(result[0]['generated_text'][len(prompt):])
```