jxiw/BiGS
Official Repository of Pretraining Without Attention (BiGS), BiGS is the first model to achieve BERT-level transfer learning on the GLUE benchmark with subquadratic complexity in length (or without attention).
Star & Fork Trend (116 data points)
Multi-Source Signals
Growth Velocity
jxiw/BiGS has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | BiGS | nagato-ai | STAMP | dashscope-sdk |
|---|---|---|---|---|
| Stars | 118 | 118 | 118 | 118 |
| Forks | 8 | 10 | 52 | 13 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Python | C# |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | MIT | MIT | MIT |
Capability Radar vs nagato-ai
Last code push 766 days ago.
Fork-to-star ratio: 6.8%. Lower fork ratio may indicate passive usage.
Issue data not yet available.
No measurable growth in the current period (first-day cold start expected).
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.
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