quantization / llm-awq /scripts /nvila_example.sh
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# run AWQ search
python -m awq.entry --model_path PATH/TO/NVILA \
--smooth_scale --media_path https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-VL/space_woaudio.mp4 \
--act_scale_path awq_cache/NVILA-VT-smooth-scale.pt --vila-20 \
--w_bit 4 --q_group_size 128 \
--run_awq --dump_awq awq_cache/NVILA.pt
# generate real quantized weights (w4)
python -m awq.entry --model_path PATH/TO/NVILA/llm \
--w_bit 4 --q_group_size 128 \
--load_awq awq_cache/NVILA.pt \
--q_backend real --dump_quant quant_cache/NVILA-w4-g128-awq.pt --vila-20