RE
finegrain-ai/refiners
A microframework on top of PyTorch with first-class citizen APIs for foundation model adaptation
834 65 +0/wk
GitHub
background-generation background-removal controlnet diffusion-models dinov2 image-generation ip-adapter lcm lcm-lora lora sam sdxl
Trend
0
Star & Fork Trend (19 data points)
Stars
Forks
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Growth Velocity
finegrain-ai/refiners has +0 stars this period . Velocity data will be available after more historical data is collected.
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| Metric | refiners | emoca | papers-with-annotations | awesome-multi-task-learning |
|---|---|---|---|---|
| Stars | 834 | 833 | 831 | 829 |
| Forks | 65 | 103 | 74 | 65 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | N/A | N/A |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | NOASSERTION | MIT | N/A |
Capability Radar vs emoca
refiners
emoca
Maintenance Activity 0
Last code push 203 days ago.
Community Engagement 39
Fork-to-star ratio: 7.8%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.