How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_M# Run inference directly in the terminal:
llama cli -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_MUse 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 BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_M# Run inference directly in the terminal:
./llama-cli -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_MBuild 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 BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_M# Run inference directly in the terminal:
./build/bin/llama-cli -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_MUse Docker
docker model run hf.co/BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_MQuick Links
About
In the repository you can find only quantized versions of https://huggingface.co/CYFRAGOVPL/Llama-PLLuM-70B-instruct model. I am not the author of the model. I just converted to GGUF and quantized models.
Available versions
- Q4_K_M
- Q8
- Downloads last month
- 2
Hardware compatibility
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4-bit
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Base model
CYFRAGOVPL/Llama-PLLuM-70B-instruct-2412
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_M# Run inference directly in the terminal: llama cli -hf BMarcin/Llama-PLLuM-70B-chat-GGUF:Q4_K_M