MiniCPM-V, a multimodal large language model project, has seen significant updates in documentation and feature enhancements over the past 30 days, reflecting a strong focus on usability and performance optimization.
The MiniCPM-V project aims to advance vision-language understanding with models capable of processing images and video inputs. It is designed for deployment across various platforms, including mobile devices.
Recent issues and pull requests (PRs) indicate a focus on improving fine-tuning processes and addressing user-reported bugs. Notable issues include #587, which highlights problems with image token handling, and #585, concerning instability during full model fine-tuning. These issues suggest challenges in model configuration and usability.
Summary
Quantified Reports
Detailed Reportseval_mm modifications.wechat.md for WeChat integration.eval_mm changes, collaborating with Cui Junbo.2.6-sft branch with fine-tuning updates.Documentation Emphasis: Extensive updates to documentation files like README.md and wechat.md highlight a commitment to clarity and user guidance.
Collaborative Efforts: Effective collaboration is evident in joint PRs and merges, particularly between Cui Junbo and Haoyu Li.
Streamlit Enhancements: JamePeng's work on the Streamlit interface reflects ongoing efforts to improve user experience.
Active Branching for Fine-Tuning: The 2.6-sft branch indicates focused efforts on optimizing model performance through fine-tuning.
Overall, the MiniCPM-V project is actively evolving with a strong emphasis on improving both functionality and user experience.
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 19 | 24 | 21 | 17 | 1 |
| 14 Days | 30 | 28 | 30 | 25 | 1 |
| 30 Days | 98 | 72 | 169 | 84 | 1 |
| All Time | 517 | 453 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| Haoyu Li |  |
1 | 1/1/0 | 1 | 69 | 9971 |
| JamePeng |  |
1 | 0/1/0 | 4 | 1 | 182 |
| Tianyu Yu |  |
1 | 0/0/0 | 5 | 5 | 79 |
| LDLINGLINGLING |  |
1 | 0/0/0 | 10 | 5 | 12 |
| Yu-won Lee (2U1) | 0 | 1/0/0 | 0 | 0 | 0 | |
| Cui Junbo |  |
0 | 0/0/0 | 0 | 0 | 0 |
| Glenn Fernandes (glenn124f) | 0 | 0/0/1 | 0 | 0 | 0 | |
| None (jackyjinjing) | 0 | 1/0/0 | 0 | 0 | 0 | |
| Mandlin Sarah (mandlinsarah) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The MiniCPM-V project has seen a surge in recent activity, with 64 open issues currently logged. Notably, many of these issues revolve around bugs related to fine-tuning and inference, particularly concerning the handling of image tokens and memory management during training. There is a clear trend of users encountering difficulties with model performance and configuration, suggesting that while the model's capabilities are robust, its usability may require further refinement.
Several issues highlight common problems, such as discrepancies in expected input formats and errors related to tensor dimensions during training and inference. This indicates potential gaps in documentation or implementation that could hinder user experience.
Issue #587: [BUG] 在funetune/dataset.py中报告image start token != image end tokens的错误
Issue #586: How to use the forward call?
Issue #585: 全量微调vision端不稳定
Issue #584: How not to save the files in global_step1 during training
Issue #582: how to modify the system prompt
Issue #578: [BUG] finetune minicpm error
Issue #577: Finetuning issue
Issue #576: [BUG] problem when awq self-quantization
Issue #575: [BUG] Screenshot of code. OCR does not result in correct code
Issue #574: 是否可以透漏in-context learning是怎么训练的吗
Many recent issues focus on bugs related to image token handling, particularly the mismatch between image start and end tokens (#587). This suggests that users are struggling with the input format required by the model, which could lead to confusion and inefficiencies in fine-tuning processes.
The inquiry regarding how to use the forward call (#586) indicates a need for clearer documentation or examples on utilizing model methods effectively.
The issue concerning instability during full model fine-tuning (#585) raises concerns about the robustness of training configurations, especially when users report poor loss curves and performance metrics.
A recurring theme is the need for better guidance on configuring training parameters and understanding model outputs, as evidenced by multiple requests for clarification on expected behaviors during inference and fine-tuning.
The MiniCPM-V project is experiencing active engagement from its user base, with a significant number of issues reflecting both technical challenges and requests for improved usability. Addressing these concerns through enhanced documentation, clearer examples, and potential bug fixes will be crucial for maintaining user satisfaction and fostering continued development within this rapidly evolving project.
The analysis of the pull requests (PRs) for the MiniCPM-V project reveals a dynamic and active development environment. The project has seen a significant number of contributions, both in terms of new features and bug fixes, indicating a responsive approach to community feedback and an ongoing effort to enhance the model's capabilities.
vision_lr and resampler_lr) during fine-tuning. This PR is significant as it aims to improve fine-tuning performance based on user experiences and external research.flash_atten on MPS. This PR is important for users relying on specific hardware configurations.requirements.txt to include additional packages needed for fine-tuning, ensuring users have all necessary dependencies.web_demo_streamlit_2.5.py related to text mode interactions.The pull requests reflect several key themes in the development of MiniCPM-V:
Active Community Engagement: The number of open and closed PRs indicates a vibrant community contributing to the project. Contributions range from bug fixes and feature additions to documentation improvements, showcasing diverse engagement from users and developers alike.
Focus on Usability and Performance Enhancements: Many PRs aim to enhance usability (e.g., clearer error messages, better documentation) and performance (e.g., fine-tuning improvements, hardware compatibility fixes). This focus suggests a commitment to providing a robust and user-friendly tool.
Rapid Iteration and Responsiveness: The quick turnaround from PR creation to closure (often within days) highlights an efficient review process and responsiveness to emerging issues or feature requests.
Diverse Contributions Addressing Various Aspects of the Project:
Global Reach and Accessibility Efforts: The addition of Japanese translations in PR #435 reflects efforts to make the project accessible to a broader audience.
In conclusion, the pull request activity in the MiniCPM-V project demonstrates a well-managed open-source initiative with active community involvement, continuous improvement efforts, and a strong focus on usability and performance optimization. The project's ability to rapidly address issues and incorporate new features is indicative of its healthy development lifecycle.
Cui Junbo (Cuiunbo)
eval_mm for MiniCPM-V 2.6, with extensive changes across multiple files (9971 lines added).LDLINGLINGLING
wechat.md and adding images related to WeChat integration.Haoyu Li (lihytotoro)
eval_mm for MiniCPM-V 2.6.JamePeng
Tianyu Yu (yiranyyu)
Qianyu Chen (qyc-98)
2.6-sft branch with multiple updates related to fine-tuning and README modifications.Hongji Zhu (iceflame89)
Jacky Jin Jing, Mandlin Sarah, 2U1, Glenn124f
Documentation Focus: A significant amount of recent activity revolves around updating documentation (README.md, wechat.md), indicating a strong emphasis on user guidance and project clarity.
Collaborative Merging: Multiple merges indicate effective collaboration among team members, particularly between Cui Junbo and Haoyu Li regarding the eval_mm modifications.
Feature Enhancements: JamePeng's updates reflect ongoing efforts to enhance the Streamlit interface for improved user experience, showcasing a focus on usability alongside backend improvements.
Active Branching: The presence of an active branch (2.6-sft) suggests ongoing work on fine-tuning capabilities, which aligns with the project's goals of optimizing performance across various platforms.
The development team is actively engaged in enhancing both functionality and documentation of the MiniCPM-V project. Recent activities highlight a collaborative environment with a focus on improving user experience through comprehensive documentation and feature enhancements. The project appears to be well-positioned for continued growth and adaptation based on user feedback and technological advancements.