jd-opensource/xllm
Sep 2025 – Sep 2025
1 Month active
Languages Used
C++Pythonprotobuf
Technical Skills
API DesignAPI DevelopmentBackend DevelopmentBatch ProcessingC++C++ Development
yiming-l21
PROFILE
Yiming-l21
Yiming Liu developed a production-ready Flux Multimodal Image Generation Pipeline for the jd-opensource/xllm repository, integrating CLIP text models, T5 encoders, VAEs, and DiT diffusion models into a scalable, end-to-end system. The work included designing a dedicated API interface in Python and C++ to support batched inference and efficient image rendering workflows. Liu addressed scheduler and input handling bugs, improving prompt management and batch size handling within the Flux pipeline. By leveraging deep learning, distributed systems, and CUDA, Liu delivered a robust backend that enables reliable, high-throughput image generation for multimodal AI applications, demonstrating strong technical depth in model integration.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
7Total
Bugs
1
Commits
7
Features
1
Lines of code
12,141
Activity Months1
Your Network
76 people
Work History
September 2025
7 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for jd-opensource/xllm focused on delivering a scalable, end-to-end image generation capability and stabilizing the Flux-based pipeline. Highlights include the first production-ready Flux Multimodal Image Generation Pipeline (DiT diffusion) with API access and batched inference, alongside robust input handling and bug fixes that improve reliability for batch prompts.
7 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for jd-opensource/xllm focused on delivering a scalable, end-to-end image generation capability and stabilizing the Flux-based pipeline. Highlights include the first production-ready Flux Multimodal Image Generation Pipeline (DiT diffusion) with API access and batched inference, alongside robust input handling and bug fixes that improve reliability for batch prompts.
September 2025
Activity
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Quality Metrics
Correctness87.0%
Maintainability81.4%
Architecture87.2%
Performance77.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Pythonprotobuf
Technical Skills
API DesignAPI DevelopmentBackend DevelopmentBatch ProcessingC++C++ DevelopmentCMakeCUDAComputer VisionData StructuresDeep LearningDiffusion ModelsDistributed SystemsImage GenerationMachine Learning
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