OpenNLPLab / ETSC-Exact-Toeplitz-to-SSM-ConversionLinks
[EMNLP 2023] Official implementation of the algorithm ETSC: Exact Toeplitz-to-SSM Conversion our EMNLP 2023 paper - Accelerating Toeplitz Neural Network with Constant-time Inference Complexity
☆14Updated 2 years ago
Alternatives and similar repositories for ETSC-Exact-Toeplitz-to-SSM-Conversion
Users that are interested in ETSC-Exact-Toeplitz-to-SSM-Conversion are comparing it to the libraries listed below
Sorting:
- [ICLR 2023] Official implementation of Transnormer in our ICLR 2023 paper - Toeplitz Neural Network for Sequence Modeling☆80Updated last year
- Fine-Tuning Pre-trained Transformers into Decaying Fast Weights☆19Updated 3 years ago
- Reference implementation of "Softmax Attention with Constant Cost per Token" (Heinsen, 2024)☆24Updated last year
- ☆19Updated 2 years ago
- ☆20Updated last year
- sigma-MoE layer☆20Updated last year
- ☆31Updated last year
- [NeurIPS 2023 spotlight] Official implementation of HGRN in our NeurIPS 2023 paper - Hierarchically Gated Recurrent Neural Network for Se…☆65Updated last year
- Here we will test various linear attention designs.☆61Updated last year
- HGRN2: Gated Linear RNNs with State Expansion☆55Updated last year
- [NeurIPS 2022] Your Transformer May Not be as Powerful as You Expect (official implementation)☆33Updated 2 years ago
- [EMNLP 2022] Official implementation of Transnormer in our EMNLP 2022 paper - The Devil in Linear Transformer☆63Updated 2 years ago
- Official code for the paper "Attention as a Hypernetwork"☆46Updated last year
- Code for NeurIPS 2023 paper "Non-autoregressive Machine Translation with Probabilistic Context-free Grammar".☆11Updated last year
- ☆48Updated last year
- ☆11Updated 2 years ago
- Code for the paper "Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns"☆18Updated last year
- Unofficial implementation of paper : Exploring the Space of Key-Value-Query Models with Intention☆12Updated 2 years ago
- Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"☆27Updated last year
- ☆56Updated last year
- Official Repository for Efficient Linear-Time Attention Transformers.☆18Updated last year
- ☆28Updated last year
- [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning☆31Updated 2 years ago
- [EMNLP 2023]Context Compression for Auto-regressive Transformers with Sentinel Tokens☆25Updated 2 years ago
- Explorations into adversarial losses on top of autoregressive loss for language modeling☆38Updated 8 months ago
- [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling☆39Updated last year
- ☆23Updated last year
- Awesome Triton Resources☆36Updated 6 months ago
- Combining SOAP and MUON☆16Updated 9 months ago
- Triton implement of bi-directional (non-causal) linear attention☆56Updated 9 months ago