Instructions to use Mittai17/meddoc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Mittai17/meddoc with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Mittai17/meddoc:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mittai17/meddoc:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Mittai17/meddoc:Q4_K_M # Run inference directly in the terminal: llama cli -hf Mittai17/meddoc: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 Mittai17/meddoc:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Mittai17/meddoc: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 Mittai17/meddoc:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Mittai17/meddoc:Q4_K_M
Use Docker
docker model run hf.co/Mittai17/meddoc:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Mittai17/meddoc with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mittai17/meddoc" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mittai17/meddoc", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Mittai17/meddoc:Q4_K_M
- Ollama
How to use Mittai17/meddoc with Ollama:
ollama run hf.co/Mittai17/meddoc:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Mittai17/meddoc with Docker Model Runner:
docker model run hf.co/Mittai17/meddoc:Q4_K_M
- Lemonade
How to use Mittai17/meddoc with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Mittai17/meddoc:Q4_K_M
Run and chat with the model
lemonade run user.meddoc-Q4_K_M
List all available models
lemonade list
- Atomic Chat
meddoc
A vision + text medical assistant by Mittai17, built for rural and village settings in India. Talk to it in English, Tamil, or Tanglish and it replies in the same language.
Designed to give clear, safe, practical first-line advice and tell you exactly when to get professional help:
- PRECAUTIONS โ what to do right now and what NOT to do
- SOLUTIONS โ simple step-by-step instructions for home care (in order)
- WHEN TO GET HELP โ warning signs meaning go to hospital or call an ambulance
Always includes the right emergency numbers: 112 (national), 108 (ambulance), 102 / 104 (health helplines), 100 (police), 101 (fire).
meddoc also understands images โ share a photo (skin, wound, X-ray, lab report) and it will
describe what it sees and advise what to do next.
Files
| File | Description |
|---|---|
medgemma1.5-meddoc-Q4_K_M.gguf |
GGUF model (Q4_K_M, 3.3 GB) |
Modelfile |
Ollama Modelfile with the doctor system prompt |
Use with Ollama
ollama create meddoc -f Modelfile
ollama run meddoc # text
ollama run meddoc "what does this x-ray show?" (attach an image in Open WebUI)
Notes
Adapted from Google's MedGemma 1.5, which is subject to the
Health AI Developer Foundations Terms of Use.
meddoc is a starting point, not a clinical diagnosis tool โ when in doubt, go to a hospital.
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