| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| README.md | 2026-07-18 | 955 Bytes | |
| v0.3.22 source code.tar.gz | 2026-07-18 | 1.3 MB | |
| v0.3.22 source code.zip | 2026-07-18 | 1.5 MB | |
| Totals: 3 Items | 2.8 MB | 0 | |
What's Changed
Fix: autothink, thinkdeeper and deepconf for transformers >= 5 (#320)
Since transformers 5, apply_chat_template(return_tensors="pt") returns a BatchEncoding rather than a plain tensor, so passing the result straight to model(input_ids=...) raised. The tensor is now unwrapped via .input_ids:
optillm/thinkdeeper.pyoptillm/autothink/processor.pyoptillm/deepconf/processor.py
The unwrap is chained with the existing device transfer (.input_ids.to(self.model.device)) so tokens still land on the model's device — Tensor.to() returns a new tensor rather than mutating in place, so the assignment matters on CUDA/MPS.
Thanks to @jacquerie for diagnosing and reporting this.
README: dropped the GitHub stars badge and switched the downloads badge to pepy.tech, which reports actual download counts.
Full Changelog: https://github.com/algorithmicsuperintelligence/optillm/compare/v0.3.21...v0.3.22