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/WizardLM-2-8x22B-iMat-GGUF:# Run inference directly in the terminal:
llama cli -hf InferenceIllusionist/WizardLM-2-8x22B-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/WizardLM-2-8x22B-iMat-GGUF:# Run inference directly in the terminal:
./llama-cli -hf InferenceIllusionist/WizardLM-2-8x22B-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/WizardLM-2-8x22B-iMat-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf InferenceIllusionist/WizardLM-2-8x22B-iMat-GGUF:Use Docker
docker model run hf.co/InferenceIllusionist/WizardLM-2-8x22B-iMat-GGUF:Quick Links
Wizard-LM-2-8x22-iMat-GGUF
Quantized from fp32 with love. If you're using the latest version of llama.cpp you should no longer need to combine files before loading.
- Importance matrix calculated using fp16 precision model
- Calculated in 105 chunks with n_ctx=512 using groups_merged.txt
- See below for imatrix calculation arguments
.\llama-imatrix -m .\models\WizardLM-2-8x22b\ggml-model-f16.gguf -f .\imatrix\groups_merged.txt -o .\models\WizardLM-2-8x22b\WizardLM-2-8x22b-f16.imatrix -ngl 14 -t 24
For a brief rundown of iMatrix quant performance please see this PR
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.
BFloat16 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/WizardLM-2-8x22B-iMat-GGUF:# Run inference directly in the terminal: llama cli -hf InferenceIllusionist/WizardLM-2-8x22B-iMat-GGUF: