PT
THUDM/P-tuning
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
938 114 +0/wk
GitHub
few-shot-learning natural-language-processing p-tuning parameter-efficient-learning pre-trained-language-models prompt-tuning
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Star & Fork Trend (34 data points)
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| Metric | P-tuning | Eagle | langcorn | ML-University |
|---|---|---|---|---|
| Stars | 938 | 938 | 938 | 937 |
| Forks | 114 | 50 | 71 | 120 |
| Weekly Growth | +0 | +0 | -1 | +0 |
| Language | Python | Python | Python | N/A |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | MIT | N/A |
Capability Radar vs Eagle
P-tuning
Eagle
Maintenance Activity 0
Last code push 1280 days ago.
Community Engagement 61
Fork-to-star ratio: 12.2%. Active community forking and contributing.
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.