Riad Disease Gpt
A lightweight medical question-answering model trained on disease-related queries.
Model Details
- Type: Custom GPT-style Transformer
- Language: English
- Parameters: ~5M
- Architecture: 6-layer Transformer with 8 attention heads
- Vocab Size: 2500 (SentencePiece)
- Context Length: 512 tokens
Usage
from transformers import AutoModel, AutoTokenizer
import sentencepiece as spm
# Load model
model = AutoModel.from_pretrained("riadrayhan111/riad-disease-gpt", trust_remote_code=True)
tokenizer = spm.SentencePieceProcessor()
tokenizer.load('riadrayhan111/riad-disease-gpt/tokenizer.model')
# Generate response
class SimpleTokenizer:
def __init__(self, sp_model):
self.sp = sp_model
self.eos_token_id = 2
def encode(self, text):
return self.sp.encode(text)
def decode(self, tokens):
return self.sp.decode(tokens)
tok = SimpleTokenizer(tokenizer)
answer = model.generate_text(tok, "What is fever?", max_length=100)
print(answer)
Training
Trained on a custom medical dataset focused on common diseases, symptoms, and treatments.
Limitations
โ ๏ธ Important: This model is for educational purposes only.
- Not a substitute for professional medical advice
- Limited to information in training data
- Should not be used for medical diagnosis
License
Apache 2.0
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