dccuchile/wefe

WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!

182 14 +0/wk

GitHub

bias-detection bias-reduction fairness-ai fairness-ml library nlp nlp-library python3 word-embedding-evaluation word-embedding-fairness word-embeddings

Trend 0

Star & Fork Trend (18 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 182

forks 14

Growth Velocity

dccuchile/wefe 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	wefe	RAG-SaaS	multihead-siamese-nets	GraTAG
Stars	182	182	183	181
Forks	14	30	43	15
Weekly Growth	+0	+0	+0	+99
Language	Python	TypeScript	Jupyter Notebook	Python
Sources	1	1	1	1
License	MIT	NOASSERTION	MIT	NOASSERTION

Capability Radar vs RAG-SaaS

wefe

RAG-SaaS

Maintenance Activity 26

Last code push 135 days ago.

Community Engagement 38

Fork-to-star ratio: 7.7%. 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 MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.