Alternatives and similar repositories for CoPE-cuda

Users that are interested in CoPE-cuda are comparing it to the libraries listed below

• HazyResearch / prefix-linear-attention
  ☆55Updated last year
• princeton-pli / MeCo
  Code for ICML 25 paper "Metadata Conditioning Accelerates Language Model Pre-training (MeCo)"
  ☆40Updated 2 weeks ago
• renll / SeqBoat
  [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling
  ☆37Updated last year
• Aleph-Alpha-Research / NeurIPS-WANT-submission-efficient-parallelization-layouts
  ☆22Updated last year
• jungokasai / T2R
  ☆14Updated 2 years ago
• OpenNLPLab / LASP
  Linear Attention Sequence Parallelism (LASP)
  ☆85Updated last year
• dangxingyu / rnn-icrag
  Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"
  ☆27Updated last year
• YuchuanTian / RethinkTinyLM
  [ICML'24] The official implementation of “Rethinking Optimization and Architecture for Tiny Language Models”
  ☆121Updated 6 months ago
• kyegomez / Blockwise-Parallel-Transformer
  32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.
  ☆48Updated 2 years ago
• NormXU / Consistent-DynamicNTKRoPE
  An Experiment on Dynamic NTK Scaling RoPE
  ☆64Updated last year
• OpenNLPLab / HGRN
  [NeurIPS 2023 spotlight] Official implementation of HGRN in our NeurIPS 2023 paper - Hierarchically Gated Recurrent Neural Network for Se…
  ☆66Updated last year
• kyegomez / LM-Infinite
  Implementation of "LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models"
  ☆41Updated 8 months ago
• sustcsonglin / mamba-triton
  ☆48Updated last year
• sunyt32 / torchscale
  Transformers at any scale
  ☆41Updated last year
• locuslab / scaling_laws_data_filtering
  ☆64Updated last year
• kamanphoebe / Look-into-MoEs
  [NAACL 2025] A Closer Look into Mixture-of-Experts in Large Language Models
  ☆52Updated 5 months ago
• kyegomez / Infini-attention
  Implementation of the paper: "Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention" from Google in pyTO…
  ☆55Updated 2 weeks ago
• YuchuanTian / DiJiang
  [ICML'24 Oral] The official code of "DiJiang: Efficient Large Language Models through Compact Kernelization", a novel DCT-based linear at…
  ☆101Updated last year
• frankxwang / dpo-prefix-sharing
  DPO, but faster 🚀
  ☆43Updated 7 months ago
• VITA-Group / Data-Efficient-Scaling
  [ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang
  ☆14Updated last year
• AntNLP / nope_head_scale
  ☆24Updated last year
• RobertCsordas / moe
  Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"
  ☆38Updated last month
• qiuzh20 / gated_attention
  The official implementation for Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
  ☆44Updated 2 months ago
• NonvolatileMemory / flash_attn_gqa
  triton ver of gqa flash attn, based on the tutorial
  ☆11Updated 11 months ago
• amirzandieh / HyperAttention
  Triton Implementation of HyperAttention Algorithm
  ☆48Updated last year
• chijames / KERPLE
  ☆19Updated 2 years ago
• OpenNLPLab / Transnormer
  [EMNLP 2022] Official implementation of Transnormer in our EMNLP 2022 paper - The Devil in Linear Transformer
  ☆61Updated last year
• berlino / gated_linear_attention
  ☆105Updated last year
• kyo-takano / chinchilla
  A toolkit for scaling law research ⚖
  ☆50Updated 5 months ago
• yikangshen / megablocks
  ☆20Updated last year