epfl-llm/guidelines
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How to use chrohi/meditron-7b-Q8_0-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="chrohi/meditron-7b-Q8_0-GGUF", filename="meditron-7b-q8_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
How to use chrohi/meditron-7b-Q8_0-GGUF with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0
# 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 chrohi/meditron-7b-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0
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 chrohi/meditron-7b-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf chrohi/meditron-7b-Q8_0-GGUF:Q8_0
docker model run hf.co/chrohi/meditron-7b-Q8_0-GGUF:Q8_0
How to use chrohi/meditron-7b-Q8_0-GGUF with Ollama:
ollama run hf.co/chrohi/meditron-7b-Q8_0-GGUF:Q8_0
How to use chrohi/meditron-7b-Q8_0-GGUF 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 chrohi/meditron-7b-Q8_0-GGUF 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 chrohi/meditron-7b-Q8_0-GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for chrohi/meditron-7b-Q8_0-GGUF to start chatting
How to use chrohi/meditron-7b-Q8_0-GGUF with Docker Model Runner:
docker model run hf.co/chrohi/meditron-7b-Q8_0-GGUF:Q8_0
How to use chrohi/meditron-7b-Q8_0-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull chrohi/meditron-7b-Q8_0-GGUF:Q8_0
lemonade run user.meditron-7b-Q8_0-GGUF-Q8_0
lemonade list
This model was converted to GGUF format from epfl-llm/meditron-7b using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Install llama.cpp through brew.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI. CLI:
llama-cli --hf-repo chrohi/meditron-7b-Q8_0-GGUF --model meditron-7b-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo chrohi/meditron-7b-Q8_0-GGUF --model meditron-7b-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && \
cd llama.cpp && \
make && \
./main -m meditron-7b-q8_0.gguf -n 128
8-bit
Base model
meta-llama/Llama-2-7b