Comments (3)
Do you have WSL2 installed?
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@ekinox971 - if you use pip debug --verbose
it will output the compatible tags for your set up.
I suspect that because you're on Python 3.12 and the tagged versions on PyPI aren't for 3.12 (see here) pip is failing to find something it thinks it can install.
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If you're able to downgrade to 3.11 without too much difficulty that should resolve things.
I had a similar(ish) situation with 3.12 on Arch and I tried compiling too but ran into problems and opting to switch to 3.11 was the easy workaround. YMMV of course!
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Related Issues (20)
- 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
- Questions: scales less than 1
- deepseek-v2-coder-lite awq converting HOT 1
- raise Exception (the loss increases to NAN ) when quantilizing DeepSeek-V2-chat using the new version of AutoAWQ in the sub-iteration (18/60) HOT 4
- LookupError: unknown encoding: unicode
- GGUF export example hangs on AWQ step
- support of fake backend
- baichuan2-7B-Chat awq fuse_layer=True error
- Discussion on the selection of the calibration data set
- get a problem when quantize the model Llama-3-Taiwan-70B-Instruct on one RTX-4090. HOT 2
- Installation Problems: ModuleNotFoundError: No module named torch HOT 2
- awq quantization is not fully optimized yet. The speed can be slower than non-quantized models HOT 2
- AutoAWQ 0.2.5 received a retroactive update that added PyTorch 2.3 as a requirement HOT 5
- CUDA error: no kernel image is available for execution on the device HOT 1
- Quantitative model report wrong, RuntimeError: Expected all tensors to be on the same device HOT 7
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