Summary for 2025-09: Delivered a robustness improvement in the token generation and sampling path for vllm-gaudi, reducing error scenarios during chunked prefill and long-running inference. The change focuses on preventing negative output logits and avoiding sampling when logits are not available, improving reliability and user experience in production.

In August 2025, delivered a critical reliability improvement for HabanaAI/vllm-fork by tightening HF_TOKEN handling for ModelScope integration. The fix ensures that an empty HF_TOKEN environment variable is deleted rather than set to an empty string, preserving None and preventing invalid credential errors for the Qwen1.5-0.5B-Chat model when using ModelScope. This change reduces runtime credential failures and improves developer productivity when integrating with external services.