Gemma, an open-source project by Google DeepMind, provides large language models with open weights for inference using Flax and JAX. Despite its popularity, recent activities highlight significant user challenges in installation and model evaluation.
Recent issues and pull requests (PRs) reveal ongoing development and user engagement, but also point to critical areas needing attention. Notably, several issues (#43, #42) involve installation failures and difficulties reproducing evaluation results, suggesting potential barriers to user adoption. The development team has been actively working on bug fixes and enhancements, with the Gemma Team addressing configuration issues and Michelle Casbon focusing on documentation improvements. However, contributions appear largely independent, with limited collaboration among team members.
Gemma Team
Michelle Casbon
Jasper Snoek
Kathleen Kenealy
Shreya Pathak
R Dadashi
Morgane Rivière
Alistair Muldal
Summary
Quantified Reports
Detailed Reports.ipynb format (178 days ago).| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| Gemma Team |  |
1 | 0/0/0 | 4 | 7 | 153 |
| Michelle Casbon |  |
1 | 0/0/0 | 3 | 3 | 121 |
| Frédéric Bastien (nouiz) | 0 | 0/0/1 | 0 | 0 | 0 | |
| Paige Bailey (dynamicwebpaige) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 0 | 0 | 0 | 0 | 0 |
| 30 Days | 3 | 3 | 1 | 1 | 1 |
| 90 Days | 7 | 3 | 7 | 1 | 1 |
| All Time | 29 | 9 | - | - | - |
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.
The GitHub repository for the Gemma project has seen a moderate level of recent activity, with 20 open issues currently logged. Notably, several issues are related to installation problems and model evaluation discrepancies, indicating potential challenges users face when integrating or utilizing the models. A recurring theme appears to be the difficulty in reproducing evaluation results and installation errors, which could hinder user adoption and satisfaction.
Several issues exhibit anomalies, such as the lack of responses to urgent installation problems (#43, #7) and questions about model performance (#42). The absence of timely resolutions may lead to frustration among users and could impact the project's reputation. Furthermore, there are multiple inquiries regarding specific functionalities (e.g., PPL evaluations in #44, function calling in #38), suggesting that users are actively seeking guidance on advanced features that may not be adequately documented.
Issue #44: how about ppl on wikitext?
Issue #43: pip install fail
Issue #42: Reproducing evaluations
Issue #40: Sliding Window Attention
Issue #38: Function calling with Gemma
Issue #43: pip install fail
Issue #42: Reproducing evaluations
Issue #40: Sliding Window Attention
Issue #38: Function calling with Gemma
Issue #36: MMLU script require
The issues reflect a mix of technical bugs and user inquiries, with a strong emphasis on installation difficulties and the need for clearer documentation regarding model capabilities and evaluation processes.
The repository for the Gemma project by Google DeepMind currently has 9 open pull requests (PRs) and 5 closed PRs. The contributions range from minor fixes and enhancements to significant feature additions, reflecting ongoing development and community engagement.
PR #41: Added "Open in Colab" button to each notebook in the colab directory. This enhancement improves accessibility for users wanting to run notebooks directly in Google Colab. Created 28 days ago.
PR #34: Introduced a .gitignore file to exclude unnecessary files from version control. This is a standard practice that helps maintain a clean repository. Created 90 days ago.
PR #31: Fixed a code snippet in the README related to huggingface_hub, correcting the local directory assignment. This ensures clarity and correctness in usage examples. Created 95 days ago.
PR #28: Corrected an error in the Hugging Face download code snippet in the README. This PR highlights the importance of maintaining accurate documentation for user guidance. Created 130 days ago.
PR #27: Updated sampling_tutorial.ipynb to fix a typo, which reflects attention to detail in educational materials. Created 134 days ago.
PR #25: Updated fine_tuning_tutorial.ipynb to correct variable casing issues, ensuring consistency in variable naming conventions. Created 139 days ago.
PR #24: Fixed a typo in the repository card within the README, enhancing overall documentation quality. Created 144 days ago.
PR #17: Implemented an auto-labeling workflow for issues and PRs containing the keyword "Gemma." This automation can streamline project management by categorizing contributions effectively. Created 163 days ago.
PR #3: Fixed invalid Poetry configuration in pyproject.toml, allowing successful installation of dependencies. This is crucial for maintaining a functional development environment. Created 176 days ago.
PR #39: Attempted to fix a test related to pytest but was closed without merging due to an alternative solution being found. Closed 10 days ago.
PR #19: Corrected a typo in the fine-tuning tutorial but was dropped as it was resolved through another internal method. Closed 142 days ago.
PR #15: Added instructions for downloading models from Hugging Face, which was merged successfully, enhancing user guidance on model access. Closed 144 days ago.
PR #12: Fixed a command in the README that was causing errors when executed; this PR was also merged, improving usability. Closed 170 days ago.
PR #2: Updated a broken link in the README but was not merged; however, it received positive feedback indicating community engagement with documentation accuracy. Closed 175 days ago.
The pull requests for the Gemma project exhibit several notable themes and commonalities that reflect both ongoing development efforts and community involvement.
Firstly, there is a strong emphasis on documentation accuracy and usability within the project, as evidenced by multiple PRs aimed at fixing typos or clarifying code snippets (e.g., PRs #31, #28, #27, and #24). These contributions are critical because they enhance user experience and reduce confusion for new users engaging with the project’s resources.
Secondly, there is a clear trend towards improving accessibility and usability features, such as the addition of an "Open in Colab" button (PR #41) and automated labeling workflows (PR #17). These enhancements indicate an awareness of user needs within the community, aiming to simplify interactions with the tools provided by Gemma.
Moreover, several PRs focus on maintaining best practices for software development, such as introducing a .gitignore file (PR #34) and fixing configuration issues (PR #3). These contributions are essential for ensuring that the repository remains clean and functional over time, which is particularly important given its open-source nature where many contributors may interact with it.
An interesting observation is that some PRs were closed without merging due to alternative solutions being found or because they were superseded by internal fixes (e.g., PRs #39 and #19). This suggests an active development cycle where contributors are responsive to changes and improvements made outside of public contributions.
Lastly, despite having several open PRs (9), there is also a healthy number of closed PRs (5), indicating that while there are ongoing developments, there is also progress being made towards integrating changes into the main branch. The relatively high number of stars (2345) and forks (287) further emphasizes community interest and engagement with the Gemma project.
In conclusion, the pull requests reflect a vibrant community actively contributing to enhancing both functionality and usability within the Gemma project. The focus on documentation quality, accessibility features, adherence to best practices, and responsiveness to changes showcases a collaborative effort aimed at making Gemma a robust resource for users interested in large language models.
Gemma Team
Michelle Casbon (texasmichelle)
Jasper Snoek (JasperSnoek)
Kathleen Kenealy (kkenealy)
Shreya Pathak
R Dadashi (ddsh)
Morgane Rivière (Molugan)
Alistair Muldal (alimuldal)
.ipynb files and clarified instructions for downloading checkpoints (178 days ago).The development team is engaged in refining the Gemma project through bug fixes, feature enhancements, and documentation improvements. The independent nature of recent contributions may indicate a need for more collaborative efforts moving forward.