Comments (2)
tonylins
commented on July 2, 2024
Hi, great to hear that you observe a better accuracy!
The memory usage part is weird. When we test AWQ, it uses similar memory size as GPTQ. Could you provide the script you used to run inference with AWQ? Thanks!
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lyg95
commented on July 2, 2024
Thanks for your reply. I conducted a more detailed analysis of the quantization model. I find that the aforementioned problem is not caused by the awq algorithm. It should be related to the test tasks as well as the model configuration. For the issues related to use_cache, I will analyze the code myself later.
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Related Issues (20)
- 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
- Support for Qwen models HOT 2
- AWQ for non-Transfomer Implementation HOT 3
- Error while Quantizing OWLv2 model
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