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Quantized version of this: https://huggingface.co/ausboss/llama-30b-supercot |
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GPTQ quantization using https://github.com/0cc4m/GPTQ-for-LLaMa for compatibility with 0cc4m's fork of KoboldAI |
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This one is without groupsize to save on VRAM, so that you can enjoy the full 2048 max context if you have 24GB VRAM (or at least get a lot closer to it versus the groupsize version) |
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Command used to quantize: |
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```python llama.py c:\llama-30b-supercot c4 --wbits 4 --act-order --true-sequential --save_safetensors 4bit.safetensors``` |
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Evaluation & Score (Lower is better): |
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* WikiText2: 4.66 |
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* PTB: 17.64 |
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* C4: 6.50 |
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Groupsize version is here: https://huggingface.co/tsumeone/llama-30b-supercot-4bit-128g-cuda |