GGUFs
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I take requests, feel free to drop me a line in the community posts • 31 items • Updated • 3
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 InferenceIllusionist/llama3-42b-v0-iMat-GGUF:# Run inference directly in the terminal:
llama cli -hf InferenceIllusionist/llama3-42b-v0-iMat-GGUF:Use 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 InferenceIllusionist/llama3-42b-v0-iMat-GGUF:# Run inference directly in the terminal:
./llama-cli -hf InferenceIllusionist/llama3-42b-v0-iMat-GGUF:Build 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 InferenceIllusionist/llama3-42b-v0-iMat-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf InferenceIllusionist/llama3-42b-v0-iMat-GGUF:Use Docker
docker model run hf.co/InferenceIllusionist/llama3-42b-v0-iMat-GGUF:Quick Links
llama3-42b-v0-iMat-GGUF
Quantized from fp32 with love. All credits to Charles Goddard for the original model.
- Weighted quantizations were calculated using groups_merged.txt with 105 chunks (recommended amount for this file) and n_ctx=512. Special thanks to jukofyork for sharing this process
For more information on the pruning technique utilized in this model: https://arxiv.org/abs/2403.17887
Brief rundown of iMatrix quant performance
All quants are verified working prior to uploading to repo for your safety and convenience.
Tip: Pick a size that can fit in your GPU while still allowing some room for context for best speed. You may need to pad this further depending on if you are running image gen or TTS as well.
FP16 model card can be found here
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Hardware compatibility
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf InferenceIllusionist/llama3-42b-v0-iMat-GGUF:# Run inference directly in the terminal: llama cli -hf InferenceIllusionist/llama3-42b-v0-iMat-GGUF: