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Using the currently popular gptq the 3bit quantization hurts performance much more than 4bit, but there's also awq (https://github.com/mit-han-lab/llm-awq) and squishllm (https://github.com/SqueezeAILab/SqueezeLLM) which are able to manage 3bit without as much performance drop - I hope to see them used more commonly.
Using the currently popular gptq the 3bit quantization hurts performance much more than 4bit, but there's also awq (https://github.com/mit-han-lab/llm-awq) and squishllm (https://github.com/SqueezeAILab/SqueezeLLM) which are able to manage 3bit without as much performance drop - I hope to see them used more commonly.
Related posts
- Has anyone tried out Squeezellm?
- SqueezeLLM: Dense-and-Sparse Quantization
- New quantization method SqueezeLLM allows for loseless compression for 3-bit and outperforms GPTQ and AWQ in both 3-bit and 4-bit. Quantized Vicuna and LLaMA models have been released.
- ChatGPT provides false information about people, and OpenAI can't correct it
- Insights from Finetuning LLMs for Classification Tasks