Instructions to use stanfordmimi/MedVAL-4B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stanfordmimi/MedVAL-4B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stanfordmimi/MedVAL-4B-GGUF") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stanfordmimi/MedVAL-4B-GGUF", dtype="auto") - llama-cpp-python
How to use stanfordmimi/MedVAL-4B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="stanfordmimi/MedVAL-4B-GGUF", filename="MedVAL-4B.IQ4_XS.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use stanfordmimi/MedVAL-4B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use stanfordmimi/MedVAL-4B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stanfordmimi/MedVAL-4B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stanfordmimi/MedVAL-4B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
- SGLang
How to use stanfordmimi/MedVAL-4B-GGUF 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 "stanfordmimi/MedVAL-4B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stanfordmimi/MedVAL-4B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "stanfordmimi/MedVAL-4B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stanfordmimi/MedVAL-4B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use stanfordmimi/MedVAL-4B-GGUF with Ollama:
ollama run hf.co/stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
- Unsloth Studio new
How to use stanfordmimi/MedVAL-4B-GGUF 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 stanfordmimi/MedVAL-4B-GGUF 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 stanfordmimi/MedVAL-4B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for stanfordmimi/MedVAL-4B-GGUF to start chatting
- Pi new
How to use stanfordmimi/MedVAL-4B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "stanfordmimi/MedVAL-4B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use stanfordmimi/MedVAL-4B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use stanfordmimi/MedVAL-4B-GGUF with Docker Model Runner:
docker model run hf.co/stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
- Lemonade
How to use stanfordmimi/MedVAL-4B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull stanfordmimi/MedVAL-4B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MedVAL-4B-GGUF-Q4_K_M
List all available models
lemonade list
Improve model card: Add pipeline tag and correct base model
This PR improves the model card for MedVAL-4B by enhancing its discoverability and accuracy on the Hugging Face Hub:
- Adds
pipeline_tag: text-classification: The model's core function is to assess and validate AI-generated medical text, assigning error categories and risk levels. This fits perfectly with a text classification pipeline, making the model more discoverable for relevant tasks. - Corrects
base_model: The "Model Details" section in the model card clearly states thatMedVAL-4Bis a "Transformer-based language model (Qwen3-4B)". This indicates thatQwen/Qwen3-4Bis the true base model it was fine-tuned from. The previousbase_modelvalue was self-referential, and this update provides accurate model lineage information.
No changes were made to the paper links as they already point to the arXiv paper, and per instructions, existing arXiv links do not need to be replaced with Hugging Face Paper page links.