Comments (3)
@michaelfeil AWQ/GEMM kernels can work for any linear layer. However, there is a challenge in applying it to BERT models because it lacks some scaling methods. For example, we would usually scale from a layernorm to a linear layer.
See more about the scaling of layers here:
https://github.com/casper-hansen/AutoAWQ/blob/main/awq/quantize/scale.py
I also created a PR for better scaling for Mixtral, which may be interesting to you:
#301
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Would love this for image captioning with quantized speedup.
The kosmos-2
model from Microsoft would be another good candidate
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hej @casper-hansen I would be curious to implement this for https://github.com/michaelfeil/infinity. Do you see any road-blockers in regards to encoder only architectures? Will the GEMM kernels work for non-causal masked LMs?
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Related Issues (20)
- when quantize qwen2 by autoawq, it not works successful. HOT 2
- Support Qwen2-57B-A14B?
- awqint4 to gguf ,ModuleNotFoundError: No module named 'awq.apply_awq' HOT 4
- Is there an example on how to quantize with multiple GPUs? Is it possible to quantize Llama 3 70B with 2x3090 24GB?
- I wanted to add a pull request, but it was closed immediately, prompting that the base branch is protected. HOT 2
- ConnectionError: Couldn't reach 'mit-han-lab/pile-val-backup' on the Hub (ConnectTimeout) HOT 11
- [Performance degrade]phi-3-medium-128k-instruct after awq quantized, then output repetitively HOT 2
- Support Qwen2 72 Awq quantization? HOT 2
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:7 and cuda:0! (when checking argument for argument index in method wrapper_CUDA__index_select)
- Unable to install with `poetry`
- Is it possible to quantize MoE models?
- Multi-GPU quantization randomly loads all host GPUs HOT 1
- Same AWQ model behaves differently on two similar machines
- deepseek-coder-v2-instruction-awq HOT 8
- Version on PyPi doesn't support Python 3.12 HOT 1
- Performance with PyTorch 2.3.x HOT 4
- Calibration Dataset: how to avoid computing loss on instructions?
- I encountered the following problem during the KL assessment
- Lora Adapters Support
- Gemma2 Support HOT 2
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