KingNish/reasoning-base-20k
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How to use theprint/ReWiz-Llama-3.1-8B with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M # Run inference directly in the terminal: llama cli -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M # Run inference directly in the terminal: llama cli -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M
# 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 theprint/ReWiz-Llama-3.1-8B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M
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 theprint/ReWiz-Llama-3.1-8B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf theprint/ReWiz-Llama-3.1-8B:Q4_K_M
docker model run hf.co/theprint/ReWiz-Llama-3.1-8B:Q4_K_M
How to use theprint/ReWiz-Llama-3.1-8B with Ollama:
ollama run hf.co/theprint/ReWiz-Llama-3.1-8B:Q4_K_M
How to use theprint/ReWiz-Llama-3.1-8B with Docker Model Runner:
docker model run hf.co/theprint/ReWiz-Llama-3.1-8B:Q4_K_M
How to use theprint/ReWiz-Llama-3.1-8B with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull theprint/ReWiz-Llama-3.1-8B:Q4_K_M
lemonade run user.ReWiz-Llama-3.1-8B-Q4_K_M
lemonade list
Half the data was geared towards better reasoning (EvolKit-20k and reasoning-base-20k), the other half will help to de-censor the model (WizardLM data set).
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.