AN
Hironsan/anago
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
1.5k 362 +0/wk
GitHub
deep-learning keras machine-learning named-entity-recognition natural-language-processing sequence-labeling
Trend
0
Star & Fork Trend (17 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
Hironsan/anago 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 | anago | OpenNMT-tf | CADL | Generative_Deep_Learning_2nd_Edition |
|---|---|---|---|---|
| Stars | 1.5k | 1.5k | 1.5k | 1.5k |
| Forks | 362 | 380 | 722 | 580 |
| Weekly Growth | +0 | +0 | +0 | +1 |
| Language | Python | Python | Jupyter Notebook | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | Apache-2.0 | Apache-2.0 |
Capability Radar vs OpenNMT-tf
anago
OpenNMT-tf
Maintenance Activity 0
Last code push 1218 days ago.
Community Engagement 100
Fork-to-star ratio: 24.4%. 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.