---
language:
- en
license: apache-2.0
tags:
- medical
- disease
- healthcare
- text-generation
- pytorch
- transformers
library_name: transformers
pipeline_tag: text-generation
---

# 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

```python
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

⚠️ **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