- 01 Mar, 2024 1 commit
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Robert Shaw authored
Co-authored-by:
Robert Shaw <114415538+rib-2@users.noreply.github.com> Co-authored-by:
alexm <alexm@neuralmagic.com>
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- 01 Feb, 2024 1 commit
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Kunshang Ji authored
Co-authored-by:
Jiang Li <jiang1.li@intel.com> Co-authored-by:
Kunshang Ji <kunshang.ji@intel.com>
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- 15 Jan, 2024 1 commit
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Chenhui Zhang authored
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- 15 Dec, 2023 1 commit
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CHU Tianxiang authored
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- 16 Nov, 2023 1 commit
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Zhuohan Li authored
TP/quantization/weight loading refactor part 2 - Refactor quantized linear logic and extend quantization support to all models (#1622) Refactor the tensor parallelism, quantization, and weight-loading codes. Summary of the new features enabled by this PR: - **All models** are able to be quantized with AWQ and SqueezeLLM, and [soon GPTQ](https://github.com/vllm-project/vllm/pull/1580). - Model loading code became much simpler. - Support model parallelism for all MQA/GQA models when the number of key/value heads is smaller than the tensor parallel size.
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