🛠️ Modified transformers/ Library

In local inference mode, we extend the internal decoding loop of the HuggingFace transformers library to support execution-aware generation.
Specifically, our modifications in transformers/generation/utils.py enable token-level integration of runtime feedback, allowing the model to dynamically condition on execution traces — as described in Section 3 of the paper.

✅ This work builds on the original Hugging Face Transformers repository, which is licensed under the Apache License 2.0.
The original code remains under Apache 2.0.

🔒 Only the modifications introduced by the EG-CFG Research Team are licensed under CC BY-NC-SA 4.0.
These changes are clearly marked in the source code using # --- EG-CFG Modification START --- and # --- EG-CFG Modification END --- comment blocks.
For commercial use of these modifications, please contact yair.eran@ramot.org.

Full source: github.com/boazlavon/eg_cfg