from transformers import AutoTokenizer, AutoModelForCausalLM

model = AutoModelForCausalLM.from_pretrained("dkumarcvp/medical-llm-1gb")
tokenizer = AutoTokenizer.from_pretrained("dkumarcvp/medical-llm-1gb")

# Generate medical text
prompt = "Question: What are the symptoms of diabetes?\nAnswer:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=150, temperature=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)

Disclaimer

Base Model: DistilGPT-2
Parameters: ~82M
Size: ~350MB
Domain: Medical/Healthcare
License: MIT

⚠️ For educational and research purposes only. Not for medical diagnosis or treatment.

Hardware Requirements

RAM: 2GB minimum
Storage: 1GB
Device: CPU compatible