ce5872705e
### What this PR does / why we need it?
Adds W4A16 quantization method for the Kimi-K2-Thinking model and
updates relevant modules to support the new quantization method.
- Implements complete W4A16 quantization method including weight
packing/unpacking, per-group quantization parameter generation,
post-processing logic and MoE method application.
- Adds parameters `use_int4_w4a16`, `w1_offset` and `w2_offset`, adjusts
`with_quant` conditional logic to support W4A16 matrix multiplication.
- Adds `packed_modules_model_mapping` for Kimi-K2-Thinking model and
processing logic for `weight_packed` field.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: zhoux77899 <zhouxiang100@huawei.com>
Signed-off-by: Ruri <33858552+zhoux77899@users.noreply.github.com>
Signed-off-by: Ruri <zhouxiang100@huawei.com>
vLLM Ascend Plugin documents
Live doc: https://vllm-ascend.readthedocs.io
Build the docs
# Install dependencies.
pip install -r requirements-docs.txt
# Build the docs.
make clean
make html
# Build the docs with translation
make intl
# Open the docs with your browser
python -m http.server -d _build/html/
Launch your browser and open:
- English version: http://localhost:8000
- Chinese version: http://localhost:8000/zh_CN