FI
jina-ai/finetuner
:dart: Task-oriented embedding tuning for BERT, CLIP, etc.
1.5k 68 +0/wk
GitHub
bert few-shot-learning fine-tuning finetuning jina metric-learning negative-sampling neural-search openai-clip pretrained-models siamese-network similarity-learning
Trend
0
Star & Fork Trend (32 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
jina-ai/finetuner has +0 stars this period . Velocity data will be available after more historical data is collected.
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Signal-backed technical analysis will be available soon.
| Metric | finetuner | sie | SAM-Adapter-PyTorch | Curator |
|---|---|---|---|---|
| Stars | 1.5k | 1.5k | 1.5k | 1.5k |
| Forks | 68 | 118 | 122 | 252 |
| Weekly Growth | +0 | +0 | +0 | +2 |
| Language | Python | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | Apache-2.0 | MIT | Apache-2.0 |
Capability Radar vs sie
finetuner
sie
Maintenance Activity 0
Last code push 759 days ago.
Community Engagement 69
Fork-to-star ratio: 4.5%. 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 Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.