learnables/learn2learn
A PyTorch library for meta-learning research offering few-shot learning benchmarks, MAML implementations, and differentiable optimization utilities.
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Learn2learn accelerates the meta-learning research cycle by providing low-level utilities and unified interfaces for creating new algorithms and domains. It includes high-quality implementations of existing meta-learning algorithms, standardized benchmarks for few-shot learning, and environment utilities for meta-reinforcement learning. The library maintains compatibility with standard PyTorch ecosystem tools.
Frequently asked
- What is learnables/learn2learn?
- A PyTorch library for meta-learning research offering few-shot learning benchmarks, MAML implementations, and differentiable optimization utilities.
- Is learn2learn open source?
- Yes — learnables/learn2learn is open source, released under the MIT license.
- What language is learn2learn written in?
- learnables/learn2learn is primarily written in Python.
- How popular is learn2learn?
- learnables/learn2learn has 2.9k stars on GitHub.
- Where can I find learn2learn?
- learnables/learn2learn is on GitHub at https://github.com/learnables/learn2learn.