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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| .. | ||
| __init__.py | ||
| communication_op.py | ||
| parallel_state.py | ||
| README.md | ||
| utils.py | ||
The files in this folder are ported from Megatron-LM. We only keep the codes that are used in inference.