Go ahead and axolotl questions
C-Rank Grade: B (Solid) - 47/100
External PR Merge Rate: 30%
Response Time: 10h
First Timer Success: 43%
axolotl-ai-cloud/axolotl has a recorded first-timer success rate of 42.9%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in axolotl-ai-cloud/axolotl respond to incoming external pull requests in approximately 10.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 46.8 places axolotl-ai-cloud/axolotl in the B tier.
The external contributor pull request merge rate for axolotl-ai-cloud/axolotl is 30.3%, based on public PR activity from non-core contributors.
axolotl-ai-cloud/axolotl currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Active maintainer team in axolotl-ai-cloud/axolotl welcoming community pull requests and bug fixes.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
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External PR acceptance
First PR success rate
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Description Choosing the right LoRA rank is largely trial-and-error. An automatic recommendation based on dataset size, task type, and base model would save time. Use Case New users don't know what rank to choose Different tasks benefit from different ranks (classification vs generation) Could be a --auto-rank flag or a preprocessing analysis step Based on our experience, rank 16 works for most tasks under 10K samples, but this heuristic could be formalized.
⚠️ Please check that this feature request hasn't been suggested before. I searched previous Ideas in Discussions didn't find any similar feature requests. I searched previous Issues didn't find any similar feature requests. 🔖 Feature description Hey team, Creating a separate issue for this thread. I was wondering if there were any plans for including TPU/Trainium support in the near future? Axolotl is currently on accelerate v1.13.0, which supports both platforms. I have linked relevant documentation below Trainium support was just added in 1.13.0. TPU support has existed for longer, but isn't particularly well documented. https://huggingface.co/docs/accelerate/basic_tutorials/tpu https://huggingface.co/docs/accelerate/concept_guides/training_tpu @NanoCode012 mentioned potential issues such as difficulty including the platform in dev/CI. Would be great to hear what the team thinks and if TPU would be feasible! ✔️ Solution Support the same, or a useful subset of, the fe
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When evaluating whether to contribute to axolotl-ai-cloud/axolotl, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of axolotl-ai-cloud/axolotl acknowledge new external contributions in approximately 10 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 30.3% were successfully merged into the primary branch.
axolotl-ai-cloud/axolotl has a recorded first-timer success rate of 42.9%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~10 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 46.8 places axolotl-ai-cloud/axolotl in the Solid tier.
The external pull request merge rate is 30.3%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, axolotl-ai-cloud/axolotl currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for axolotl-ai-cloud/axolotl are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.