Instructions to use GAD-Research-Lab/MedicalAI-Light-Weight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use GAD-Research-Lab/MedicalAI-Light-Weight with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="GAD-Research-Lab/MedicalAI-Light-Weight")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("GAD-Research-Lab/MedicalAI-Light-Weight", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use GAD-Research-Lab/MedicalAI-Light-Weight with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "GAD-Research-Lab/MedicalAI-Light-Weight"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GAD-Research-Lab/MedicalAI-Light-Weight",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/GAD-Research-Lab/MedicalAI-Light-Weight

SGLang

How to use GAD-Research-Lab/MedicalAI-Light-Weight with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "GAD-Research-Lab/MedicalAI-Light-Weight" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GAD-Research-Lab/MedicalAI-Light-Weight",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "GAD-Research-Lab/MedicalAI-Light-Weight" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "GAD-Research-Lab/MedicalAI-Light-Weight",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use GAD-Research-Lab/MedicalAI-Light-Weight with Docker Model Runner:
```
docker model run hf.co/GAD-Research-Lab/MedicalAI-Light-Weight
```

MedicalAI-Light-Weight / requirements.txt

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Upload models, ONNX exports and application code

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	torch>=2.0.0
	transformers>=4.36.0
	datasets>=2.14.0
	pillow>=10.0.0
	rich>=13.0.0
	questionary>=2.0.0
	psutil>=5.9.0
	tqdm>=4.65.0
	optimum>=1.12.0
	onnxscript>=0.7.0

	# Optional (auto-installed on first use):
	# opencv-python -- camera capture
	# pydicom -- DICOM file loading
	# nltk -- BLEU evaluation
	# gradio -- Web UI (pip install gradio)
	# fastapi -- REST API server (pip install "fastapi[standard]")
	# uvicorn -- ASGI server for the API