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README.md
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license: apache-2.0
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Experimental quants of 4 expert MoE mixtrals in various GGUF formats.
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Goal is to have the best performing MoE < 10gb .
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They still need training/finetuning.
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No sparsity tricks yet.
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8.4gb custom 2bit quant works ok up until 512 token length then starts looping.
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Install llama.cpp from github
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```
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git clone https://github.com/ggerganov/llama.cpp
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cd llama.cpp
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make -j
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wget https://huggingface.co/nisten/quad-mixtrals-gguf/resolve/main/4mixq2.gguf
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limit output to 500 tokens
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license: apache-2.0
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---
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#Experimental quants of 4 expert MoE mixtrals in various GGUF formats.
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##Goal is to have the best performing MoE < 10gb .
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They still need training/finetuning.
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####No sparsity tricks yet.
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8.4gb custom 2bit quant works ok up until 512 token length then starts looping.
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Install llama.cpp from github
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```bash
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`git clone https://github.com/ggerganov/llama.cpp`
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`cd llama.cpp`
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`make -j `
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`wget https://huggingface.co/nisten/quad-mixtrals-gguf/resolve/main/4mixq2.gguf`
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`./server -m 4mixq2.gguf --host "ec2-3-99-206-122.ca-central-1.compute.amazonaws.com" -c 512`
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```
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limit output to 500 tokens
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