June 2026 monthly summary for repository modelscope/data-juicer focusing on performance improvements via enhanced parallel processing for HuggingFace backend (num_proc) across vllm and Ray modes. Fixed num_proc handling to enable Ray-based parallelism by removing hard-coded top-level num_proc=1 and restoring the vllm-only guard, resulting in higher throughput and better resource utilization in multi-process deployments. This work improves scalability and efficiency of data-juicer pipelines and supports faster data preparation for downstream ML workflows. Technologies involved include Python, multiprocessing, Ray, vLLM, and HuggingFace backends.

March 2026 monthly summary for EvolvingLMMs-Lab/lmms-eval focused on delivering the Qwen 3.5 Chat Model integration to improve chat interaction and evaluation capabilities. A new model execution script was added, and the model was registered to the registry to streamline deployment and testing. The changes include an example and lint improvements as part of the integration. No major bugs were reported this period; minor issues were addressed via linting and QA checks to ensure code quality.

Month: 2026-02 Concise monthly summary for lmms-eval (EvolvingLMMs-Lab): focus on delivering business value through reliable evaluation pipelines and bug-free batched inference.

December 2025 monthly summary for the EvolvingLMMs-Lab/lmms-eval repository focused on performance refinements and evaluation tooling for multimodal LLMs. Delivered three primary features with measurable business impact, stabilized core data paths, and established a reusable benchmarking framework to accelerate future development and evaluation.

Month 2025-11: Delivered key features for multimodal inference and configuration management in lmms-eval. Focused on Qwen3-VL integration with batch processing and alignment with official results, along with MMstar/OpenCompass config refactor. Implemented critical bug fixes to stabilize batch processing and video generation parity with VideoMME, contributing to reliable benchmarking and scalable deployment.

February 2025 monthly work summary for liguodongiot/transformers. Focused on stabilizing DeepSpeed integration for Qwen2VL by fixing data type handling for cosine and sine functions to ensure compatibility with DeepSpeed, improving numerical stability and training performance.