cwm gguf
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facebooks code world models in very small quants • 3 items • Updated
How to use PsiPi/cwm-Q3_K_M-GGUF with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M # Run inference directly in the terminal: llama cli -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M # Run inference directly in the terminal: llama cli -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_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 PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M # Run inference directly in the terminal: ./llama-cli -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_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 PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
docker model run hf.co/PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
How to use PsiPi/cwm-Q3_K_M-GGUF with Ollama:
ollama run hf.co/PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
How to use PsiPi/cwm-Q3_K_M-GGUF with Docker Model Runner:
docker model run hf.co/PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
How to use PsiPi/cwm-Q3_K_M-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull PsiPi/cwm-Q3_K_M-GGUF:Q3_K_M
lemonade run user.cwm-Q3_K_M-GGUF-Q3_K_M
lemonade list
Refer to the original model card for more details on the model.
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
llama-cli --hf-repo PsiPi/cwm-Q3_K_M-GGUF --hf-file cwm-q3_k_m.gguf -p "The meaning to life and the universe is"
llama-server --hf-repo PsiPi/cwm-Q3_K_M-GGUF --hf-file cwm-q3_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo PsiPi/cwm-Q3_K_M-GGUF --hf-file cwm-q3_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo PsiPi/cwm-Q3_K_M-GGUF --hf-file cwm-q3_k_m.gguf -c 2048
3-bit
Base model
facebook/cwm