Medical & Healthcare AI
Collection
Models and datasets for medical AI research. Includes CardioEmbed embeddings for cardiology, medical LLMs, and synthetic patient datasets. • 9 items • Updated
How to use richardyoung/openbiollm with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="richardyoung/openbiollm", filename="models/openbiollm--latest.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
How to use richardyoung/openbiollm with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf richardyoung/openbiollm # Run inference directly in the terminal: llama-cli -hf richardyoung/openbiollm
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf richardyoung/openbiollm # Run inference directly in the terminal: llama-cli -hf richardyoung/openbiollm
# 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 richardyoung/openbiollm # Run inference directly in the terminal: ./llama-cli -hf richardyoung/openbiollm
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 richardyoung/openbiollm # Run inference directly in the terminal: ./build/bin/llama-cli -hf richardyoung/openbiollm
docker model run hf.co/richardyoung/openbiollm
How to use richardyoung/openbiollm with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "richardyoung/openbiollm"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "richardyoung/openbiollm",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/richardyoung/openbiollm
How to use richardyoung/openbiollm with Ollama:
ollama run hf.co/richardyoung/openbiollm
How to use richardyoung/openbiollm with Unsloth Studio:
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 richardyoung/openbiollm to start chatting
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 richardyoung/openbiollm to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for richardyoung/openbiollm to start chatting
How to use richardyoung/openbiollm with Docker Model Runner:
docker model run hf.co/richardyoung/openbiollm
How to use richardyoung/openbiollm with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull richardyoung/openbiollm
lemonade run user.openbiollm-{{QUANT_TAG}}lemonade list
Quantized build of the OpenBioLLM Llama3-8B model for biomedical question answering, packaged for Ollama / llama.cpp runtimes. This release contains the Modelfile exported from the Ollama registry plus the matching GGUF binary.
aaditya/Llama3-OpenBioLLM-8B| Variant | Size | Blob |
|---|---|---|
latest |
7.95 GB | sha256-1cdfa5be309b5c9206925746aa8fa60601b3a04bc130d85f3257b65121408178 |
ollama create openbiollm -f modelfiles/openbiollm--latest.Modelfile
ollama run openbiollm
Originally published on my Ollama profile: https://ollama.com/richardyoung/openbiollm
We're not able to determine the quantization variants.
Base model
meta-llama/Meta-Llama-3-8B