google-deepmind / randomized_positional_encodingsLinks
Randomized Positional Encodings Boost Length Generalization of Transformers
☆82Updated last year
Alternatives and similar repositories for randomized_positional_encodings
Users that are interested in randomized_positional_encodings are comparing it to the libraries listed below
Sorting:
- Code for the paper "The Impact of Positional Encoding on Length Generalization in Transformers", NeurIPS 2023☆136Updated last year
- [NeurIPS 2023 spotlight] Official implementation of HGRN in our NeurIPS 2023 paper - Hierarchically Gated Recurrent Neural Network for Se…☆66Updated last year
- Griffin MQA + Hawk Linear RNN Hybrid☆88Updated last year
- some common Huggingface transformers in maximal update parametrization (µP)☆82Updated 3 years ago
- ☆49Updated last year
- ☆81Updated last year
- Sequence modeling with Mega.☆297Updated 2 years ago
- Yet another random morning idea to be quickly tried and architecture shared if it works; to allow the transformer to pause for any amount…☆53Updated last year
- Implementation of the conditionally routed attention in the CoLT5 architecture, in Pytorch☆229Updated 11 months ago
- Implementation of Infini-Transformer in Pytorch☆111Updated 7 months ago
- A fusion of a linear layer and a cross entropy loss, written for pytorch in triton.☆70Updated last year
- Recurrent Memory Transformer☆150Updated 2 years ago
- Efficient Transformers with Dynamic Token Pooling☆63Updated 2 years ago
- ☆66Updated 11 months ago
- [ICLR 2023] Official implementation of Transnormer in our ICLR 2023 paper - Toeplitz Neural Network for Sequence Modeling☆79Updated last year
- Implementation of GateLoop Transformer in Pytorch and Jax☆90Updated last year
- ☆53Updated last year
- ☆19Updated 2 years ago
- ☆56Updated last year
- Triton Implementation of HyperAttention Algorithm☆48Updated last year
- ☆118Updated last year
- ☆45Updated last year
- Official code release for "SuperBPE: Space Travel for Language Models"☆63Updated last month
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆38Updated 2 months ago
- [NeurIPS 2022] Your Transformer May Not be as Powerful as You Expect (official implementation)☆33Updated 2 years ago
- Pytorch implementation of the PEER block from the paper, Mixture of A Million Experts, by Xu Owen He at Deepmind☆127Updated last year
- Code for exploring Based models from "Simple linear attention language models balance the recall-throughput tradeoff"☆240Updated 2 months ago
- ☆148Updated 2 years ago
- ☆85Updated last year
- Official repository for the paper "SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention"☆98Updated 10 months ago