Alternatives and similar repositories for top_k_attention:

Users that are interested in top_k_attention are comparing it to the libraries listed below

• HKUNLP / efficient-attention
  [EVA ICLR'23; LARA ICML'22] Efficient attention mechanisms via control variates, random features, and importance sampling
  ☆84Updated 2 years ago
• OpenNLPLab / Transnormer
  [EMNLP 2022] Official implementation of Transnormer in our EMNLP 2022 paper - The Devil in Linear Transformer
  ☆60Updated last year
• Noahs-ARK / RFA
  ☆33Updated 4 years ago
• berlino / gated_linear_attention
  ☆102Updated last year
• sanagno / adaptively_sparse_attention
  ☆21Updated last year
• teelinsan / parallel-decoding
  Repository of the paper "Accelerating Transformer Inference for Translation via Parallel Decoding"
  ☆116Updated last year
• changlin31 / AutoProg
  (CVPR 2022) Automated Progressive Learning for Efficient Training of Vision Transformers
  ☆25Updated last month
• microsoft / SparseMixer
  Sparse Backpropagation for Mixture-of-Expert Training
  ☆29Updated 9 months ago
• hwang595 / Cuttlefish
  The implementation for MLSys 2023 paper: "Cuttlefish: Low-rank Model Training without All The Tuning"
  ☆44Updated last year
• lucidrains / memformer
  Implementation of Memformer, a Memory-augmented Transformer, in Pytorch
  ☆115Updated 4 years ago
• microsoft / Stochastic-Mixture-of-Experts
  This package implements THOR: Transformer with Stochastic Experts.
  ☆61Updated 3 years ago
• varunnair18 / FISH
  Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
  ☆58Updated 3 years ago
• kyegomez / Blockwise-Parallel-Transformer
  32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.
  ☆47Updated last year
• VITA-Group / Random-MoE-as-Dropout
  [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…
  ☆51Updated 2 years ago
• yikangshen / MoA
  Mixture of Attention Heads
  ☆44Updated 2 years ago
• ziplab / EcoFormer
  [NeurIPS 2022 Spotlight] This is the official PyTorch implementation of "EcoFormer: Energy-Saving Attention with Linear Complexity"
  ☆71Updated 2 years ago
• dguo98 / DiffPruning
  Parameter Efficient Transfer Learning with Diff Pruning
  ☆73Updated 4 years ago
• VITA-Group / Ms-PoE
  "Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding" Zhenyu Zhang, Runjin Chen, Shiw…
  ☆29Updated 11 months ago
• kssteven418 / LTP
  [KDD'22] Learned Token Pruning for Transformers
  ☆95Updated 2 years ago
• RobertCsordas / linear_layer_as_attention
  The official repository for our paper "The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns …
  ☆16Updated last year
• ylsung / vl-merging
  PyTorch codes for the paper "An Empirical Study of Multimodal Model Merging"
  ☆38Updated last year
• BaohaoLiao / mefts
  [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
  ☆31Updated last year
• Hunter-DDM / stablemoe
  Code for the ACL-2022 paper "StableMoE: Stable Routing Strategy for Mixture of Experts"
  ☆45Updated 2 years ago
• ahennequ / pytorch-custom-mma
  ☆29Updated 2 years ago
• VITA-Group / EarlyBERT
  [ACL-IJCNLP 2021] "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, …
  ☆18Updated 3 years ago
• jungokasai / T2R
  ☆14Updated 2 years ago
• yegcjs / DiffusionLLM
  Code for paper "Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning"
  ☆76Updated last year
• vvvm23 / sundae
  Unofficial PyTorch implementation of "Step-unrolled Denoising Autoencoders for Text Generation"
  ☆24Updated 2 years ago
• JeanKaddour / NoTrainNoGain
  Revisiting Efficient Training Algorithms For Transformer-based Language Models (NeurIPS 2023)
  ☆80Updated last year
• jzbjyb / ReAtt
  Retrieval as Attention
  ☆83Updated 2 years ago