Alternatives and similar repositories for mamba-scans:

Users that are interested in mamba-scans are comparing it to the libraries listed below

• sustcsonglin / gated_linear_attention_layer
  ☆33Updated last year
• sustcsonglin / mamba-triton
  ☆47Updated last year
• proger / nanokitchen
  Parallel Associative Scan for Language Models
  ☆18Updated last year
• berlino / seq_icl
  ☆51Updated 8 months ago
• HazyResearch / prefix-linear-attention
  ☆49Updated 7 months ago
• maximzubkov / fft-scan
  Efficient PScan implementation in PyTorch
  ☆15Updated last year
• glassroom / heinsen_attention
  Reference implementation of "Softmax Attention with Constant Cost per Token" (Heinsen, 2024)
  ☆24Updated 8 months ago
• Doraemonzzz / Awesome-Triton-Resources
  Awesome Triton Resources
  ☆19Updated 2 months ago
• zomux / lanmt-ebm
  lanmt ebm
  ☆11Updated 4 years ago
• dangxingyu / rnn-icrag
  Official repository of paper "RNNs Are Not Transformers (Yet): The Key Bottleneck on In-context Retrieval"
  ☆25Updated 9 months ago
• shikaiqiu / compute-better-spent
  ☆51Updated 4 months ago
• shawntan / stickbreaking-attention
  Stick-breaking attention
  ☆42Updated last month
• sjelassi / transformers_ssm_copy
  ☆30Updated 11 months ago
• srush / mamba-primer
  ☆37Updated 10 months ago
• yikangshen / megablocks
  ☆18Updated 8 months ago
• RakitinDen / pytorch-recursive-gumbel-max-trick
  Leveraging Recursive Gumbel-Max Trick for Approximate Inference in Combinatorial Spaces, NeurIPS 2021
  ☆10Updated 3 years ago
• amirzandieh / HyperAttention
  Triton Implementation of HyperAttention Algorithm
  ☆46Updated last year
• abhishekpanigrahi1996 / transformer_in_transformer
  ☆44Updated last year
• Doraemonzzz / xmixers
  Xmixers: A collection of SOTA efficient token/channel mixers
  ☆12Updated 3 months ago
• lucidrains / autoregressive-linear-attention-cuda
  CUDA implementation of autoregressive linear attention, with all the latest research findings
  ☆44Updated last year
• vvvm23 / mamba-jax
  Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX
  ☆82Updated last year
• srush / tangent
  Source-to-Source Debuggable Derivatives in Pure Python
  ☆15Updated last year
• tml-epfl / why-weight-decay
  Why Do We Need Weight Decay in Modern Deep Learning? [NeurIPS 2024]
  ☆60Updated 4 months ago
• RobertCsordas / ndr
  The official repository for our paper "The Neural Data Router: Adaptive Control Flow in Transformers Improves Systematic Generalization".
  ☆32Updated 3 years ago
• jopetty / word-problem
  Experiments on the impact of depth in transformers and SSMs.
  ☆22Updated 3 months ago
• srush / LLM-Talk
  ☆48Updated last year
• radarFudan / mamba-minimal-jax
  ☆30Updated 2 months ago
• renll / SeqBoat
  [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling
  ☆35Updated last year
• jenni-ai / T2FW
  Fine-Tuning Pre-trained Transformers into Decaying Fast Weights
  ☆19Updated 2 years ago
• EleutherAI / rnngineering
  Engineering the state of RNN language models (Mamba, RWKV, etc.)
  ☆32Updated 8 months ago