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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.

Co-authored-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>

Signed-off-by: Antoni Baum <antoni.baum@protonmail.com>
Co-authored-by: Viktor Ferenczi <viktor@ferenczi.eu>
Co-authored-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>

* Add py.typed so consumers of vLLM can get type checking

* Update py.typed

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Co-authored-by: aarnphm <29749331+aarnphm@users.noreply.github.com>
Co-authored-by: Zhuohan Li <zhuohan123@gmail.com>

Co-authored-by: Zhuohan Li <zhuohan123@gmail.com>

Co-authored-by: squeeze-ai-lab <squeezeailab.bair@gmail.com>
Co-authored-by: Woosuk Kwon <woosuk.kwon@berkeley.edu>