A general fine-tuning kit geared toward image/video/audio diffusion models.
C-Rank Grade: S (Elite) - 75/100
External PR Merge Rate: 94%
Response Time: 1h
First Timer Success: 86%
bghira/SimpleTuner has a recorded first-timer success rate of 85.7%. Repositories ranked S typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in bghira/SimpleTuner respond to incoming external pull requests in approximately 1.4 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 75.2 places bghira/SimpleTuner in the S tier.
The external contributor pull request merge rate for bghira/SimpleTuner is 94.1%, based on public PR activity from non-core contributors.
bghira/SimpleTuner does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Strict review standards in bghira/SimpleTuner. Ensure PR scope matches issue requirements closely before requesting review.
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External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
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Historical health & responsiveness evolution
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First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Maintainers are most responsive around 18:00 UTC (18:00 UTC in your timezone). Recommended submission window is Monday - Thursday from 16:00 to 20:00 UTC (16:00 - 20:00 UTC local).
Limited recent maintainer review activity recorded for this repository. Prediction based on heuristic baseline.
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (96% approval). Large PRs (>500 lines) take ~7 hours (42% approval). Keep your diff compact for rapid review.
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https://arxiv.org/abs/2512.24176v1 https://github.com/CVL-UESTC/Internal-Guidance It's main use is for improving sampling but it will also improve convergence speed drastically (achieves new SOTA on ImageNet) Looks simple to implement.
wandb is great to follow your training, something that the WebUI could do as well. The issue with wandb is that the free tier is quite space limited. It's fine for a few trainings but for more you need to delete the old ones and thus loose the information. On the other hand the training does have all its validation images in the output directory anyway. So it's the graphs and web page to present all of that which is missing to be able to replace wandb. So I request (mid term, not short term): have the relevant graphs and comparison of the validation images in the WebUI have that in a way that it's also visible without the WebUI, just by going into an (e.g. already archived) output directory and e.g. open a static HTML in the browser bonus request: use more efficient data formats for the images than PNG, e.g. lossless JPEG XL(*), to reduce the storage space in the archive (*) As of today JPEG XL support in the browsers is rather poor. But it's coming quickly. A different lossless form
Firstly - thank you u/bghira for this, impressive work. Premise: I've literally just finished getting the cmd line shenanigans and the ui to work - haven't got around to actually seeing if the all of the ui and the actual training is working so far (my reward is a visit to the pub, so that'll be all for today lol). Issue: I installed multiple packages to install everything and I've lost track of what the hell I've done in total - as my system has these packages installed, I can't repeat exactly what I've done, so I'm after assistance to test the method before I make a twat of myself releasing it as a fork or preferably adding it to the project, anyone ? Method: I'll supply the instructions and method, you repeat it on your system and see if it works ok for you. My concern is that with all of the installed programs I have, an install won't be repeatable. My system: 4090 24gb vram, 64gb ram on Windows 11. Notes: the instructions will include making the venv and using Python 3.12, Cuda 12
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When evaluating whether to contribute to bghira/SimpleTuner, 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 bghira/SimpleTuner acknowledge new external contributions in approximately 1 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 94.1% were successfully merged into the primary branch.
bghira/SimpleTuner has a recorded first-timer success rate of 85.7%. Repositories ranked Elite typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~1 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 75.2 places bghira/SimpleTuner in the Elite tier.
The external pull request merge rate is 94.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
bghira/SimpleTuner does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for bghira/SimpleTuner 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.