annosubmission / GRC-CacheLinks
☆16Updated 2 years ago
Alternatives and similar repositories for GRC-Cache
Users that are interested in GRC-Cache are comparing it to the libraries listed below
Sorting:
- A repository for DenseSSMs☆88Updated last year
- The this is the official implementation of "DAPE: Data-Adaptive Positional Encoding for Length Extrapolation"☆40Updated last year
- ☆24Updated last year
- [NeurIPS 2023 spotlight] Official implementation of HGRN in our NeurIPS 2023 paper - Hierarchically Gated Recurrent Neural Network for Se…☆66Updated last year
- MambaFormer in-context learning experiments and implementation for https://arxiv.org/abs/2402.04248☆58Updated last year
- HGRN2: Gated Linear RNNs with State Expansion☆56Updated last year
- [ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang☆14Updated 2 years ago
- ☆48Updated last year
- [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…☆56Updated 2 years ago
- ☆29Updated last year
- Implementation of Infini-Transformer in Pytorch☆112Updated last year
- Curse-of-memory phenomenon of RNNs in sequence modelling☆19Updated 8 months ago
- [NeurIPS 2022] Your Transformer May Not be as Powerful as You Expect (official implementation)☆34Updated 2 years ago
- Unofficial Implementation of Selective Attention Transformer☆20Updated last year
- ☆19Updated 11 months ago
- ☆26Updated last month
- User-friendly implementation of the Mixture-of-Sparse-Attention (MoSA). MoSA selects distinct tokens for each head with expert choice rou…☆28Updated 8 months ago
- [NeurIPS '25] Multi-Token Prediction Needs Registers☆26Updated 3 weeks ago
- [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models☆35Updated last year
- [ICLR 2023] Official implementation of Transnormer in our ICLR 2023 paper - Toeplitz Neural Network for Sequence Modeling☆81Updated last year
- 32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.☆49Updated 2 years ago
- PyTorch implementation of StableMask (ICML'24)☆15Updated last year
- Xmixers: A collection of SOTA efficient token/channel mixers☆28Updated 4 months ago
- Code for the paper "Cottention: Linear Transformers With Cosine Attention"☆20Updated last month
- ☆106Updated last year
- [ICLR 2025 & COLM 2025] Official PyTorch implementation of the Forgetting Transformer and Adaptive Computation Pruning☆134Updated 3 weeks ago
- ☆57Updated last year
- [ICLR 2025] Official Code Release for Explaining Modern Gated-Linear RNNs via a Unified Implicit Attention Formulation☆48Updated 10 months ago
- ☆33Updated last year
- Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"☆27Updated last year