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- FAIR Sequence Modeling Toolkit 2
- Code for "LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding", ACL 2024
- Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifically, recipes aims to provide- Consistent access to pre-trained SOTA models ready for production- Reference implementations for SOTA research reprodu…
- Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
- A modular high-level library to train embodied AI agents across a variety of tasks and environments.
- 🦾 EvalGIM (pronounced as "EvalGym") is an evaluation library for generative image models. It enables easy-to-use, reproducible automatic evaluations of text-to-image models and supports customization with user-defined metrics, datasets, and visualizations.
- A collection of MARL benchmarks based on TorchRL