Comments (1)
@StudyingShao I still can not understand this, have you figured out? In the code, we multiply each channel with a scale.
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Related Issues (20)
- `RuntimeError: probability tensor contains either `inf`, `nan` or element < 0` when running LLaVA demo HOT 2
- Llava weight
- awq_inference_engine has no attribute 'gemm_forward_cuda_new' HOT 4
- reproduce Llama2 7b failure : RuntimeError: The expanded size of the tensor (4608) must match the existing size (4096) at non-singleton dimension 3. Target sizes: [65, 32, 512, 4608]. Tensor sizes: [65, 1, 512, 4096] HOT 3
- RuntimeError: Unknown Layout in CUDA Kernel Execution
- Use awq to quantize Deepseek-coder-33B-instruct model
- run_awq.<locals>.Catcher.forward() error
- KeyError: 'llava_llama' HOT 1
- Error while generating real quantized weights for VILA
- Weight int4 quantization, but actually it is int16 HOT 4
- Possible Bug in "_search_module_scale" Function
- AWQ for non-transformer layers?
- Out of memory in Jetson Orin NX 8GB
- Inquiry about Minimum GPU Requirements HOT 1
- when q-group-size = -1,the code will not run
- Weight Packing Format
- illegal memory access when input tokens < 8
- Grok-1 AWQ
- can awq support 3-bit,2-bit, 8-bit quantization? HOT 1
- awq_inference_engine is missing from source, so quantizing custom models fails HOT 2
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