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[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
A Python package to assess and improve fairness of machine learning models.
Build LLM-powered applications in Ruby
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
Interpretability and explainability of data and machine learning models
The LLM Anti-Framework
Scalable and memory-optimized training of diffusion models
XAI - An eXplainability toolbox for machine learning
FAIR Sequence Modeling Toolkit 2