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facebookresearch/fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
32.2k 6.7k -2/wk
GitHub PyPI 2-source
artificial-intelligence python pytorch
Trend
14
Star & Fork Trend (23 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
facebookresearch/fairseq has -2 stars this period , with cross-source activity across 2 platforms (github, pypi). 7-day velocity: 0.0%.
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Maintenance Activity 0
Last code push 190 days ago.
Community Engagement 100
Fork-to-star ratio: 20.7%. 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.