Expired50% confidenceSolutionExact time
The solution is to rewrite the Dockerfile based on CUDA 12.9 and reinstall the Torch-related libraries to rebuild the image.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/13/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 10/27/2026(expired)
Sources
Related Entities
Related Claims
UnverifiedThe error 'Torch not compiled with CUDA enabled' is usually caused by installing the CPU version of PyTorch, and requires reinstalling the version corresponding to the appropriate CUDA version.73% similarUnverifiedPyTorch installed via pip by default often does not include CUDA support, and must be reinstalled by selecting the corresponding CUDA version on pytorch.org.70% similarUnverifiedThe root cause of this bug is that the official image was built on CUDA 12.9, but when installing the low-level libraries related to audio processing it mistakenly pulled in CUDA 13 components.68% similarUnverifiedThe base image used in this practical exercise was PyTorch 2.8.0 + Python 3.12 + Ubuntu + CUDA 12.8, with transformers version 5.1.0.67% similarUnverifiedThe key commit #59118 of v0.31.0rc1 involves skipping the snapshot runtime step during the build process of CUDA 12.x series images.65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1014642API
curl https://kongchang.com/api/v1/knowledge/claims/1014642MCP
get_claim(id=1014642)