* Fix VLM processor load degradation and vLLM CUDA version detection
vision.py - Fix VLM processor load for issue #4085:
- Before loading the processor, scan local config files and strip the
_Unsloth_Patched_ prefix. AutoProcessor.from_pretrained silently
degrades to a text-only tokenizer instead of raising an exception
when it encounters the unrecognized class name, so the existing
get_auto_processor fallback never triggers. Sanitizing the configs
before loading fixes backwards compat for old corrupted saves.
- After loading, detect when AutoProcessor returned a text-only
tokenizer for a VLM model (has no image_processor attribute) and
trigger the manual fallback constructor.
import_fixes.py - Fix vLLM CUDA version mismatch detection:
- _is_broken_vllm_error now also matches CUDA shared library errors
(libcudart, libcublas, libnvrtc) with "cannot open shared object
file". Previously it only matched errors containing "vllm._c" in
the message text, which missed cases where the error message was
about the missing CUDA library itself (e.g. vllm built for CUDA 12
on a CUDA 13 system).
- New _get_vllm_cuda_mismatch_message function extracts the CUDA
version from the error, compares to the system CUDA version via
torch.version.cuda, and returns a targeted install command using
the correct GitHub releases wheel URL.
- disable_broken_vllm uses the targeted message when a CUDA mismatch
is detected, falling back to the existing generic message otherwise.
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