Instructions to use syedazah777/DoctorAI-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syedazah777/DoctorAI-QA with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("syedazah777/DoctorAI-QA", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use syedazah777/DoctorAI-QA with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for syedazah777/DoctorAI-QA to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for syedazah777/DoctorAI-QA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for syedazah777/DoctorAI-QA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="syedazah777/DoctorAI-QA", max_seq_length=2048, )
DoctorAI-QA
- Developed by: syedazah777
- License: apache-2.0
- Finetuned from model: unsloth/gpt-oss-20b-unsloth-bnb-4bit
- Category: Most Useful Fine-Tune (Healthcare Q&A)
This GPT-OSS model was fine-tuned 2x faster with Unsloth and Hugging Face's TRL library for healthcare question-answering.
It is optimized to answer questions related to:
- Diabetes, Hypertension, Heart Health
- Common medical queries
- General healthcare advice
🚀 Features
- LoRA-based fine-tuning for memory-efficient training
- Quantized GPT-OSS for faster inference
- Easy-to-use Gradio interface for interactive testing
- Fully compatible with Hugging Face Transformers pipeline
📌 How to Use
🔧 Install
pip install transformers accelerate
📥 Load the Model
from transformers import pipeline
generator = pipeline("text-generation", model="syedazah777/MedGPT-HealthQ")
output = generator("What are the symptoms of diabetes?")
print(output[0]['generated_text'])
☁️ Colab / Gradio
You can run the interactive demo in a Colab notebook.
Replace prompt in the code snippet above with any healthcare question.
📝 Notes
Model trained on healthcare dataset using LoRA
Intended for educational and demonstration purposes only
Not a substitute for professional medical advice
Inference Providers NEW
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Model tree for syedazah777/DoctorAI-QA
Base model
openai/gpt-oss-20b Quantized
unsloth/gpt-oss-20b-unsloth-bnb-4bit