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Found 3 papers, 3 papers with code
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
We introduce RecurrentGemma, a family of open language models which uses Google's novel Griffin architecture.
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Recurrent neural networks (RNNs) have fast inference and scale efficiently on long sequences, but they are difficult to train and hard to scale.
Acme: A Research Framework for Distributed Reinforcement Learning
These implementations serve both as a validation of our design decisions as well as an important contribution to reproducibility in RL research.
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