Alternatives and similar repositories for pam:

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

• GATECH-EIC / Linearized-LLM
  [ICML 2024] When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
  ☆30Updated 9 months ago
• Doraemonzzz / xmixers
  Xmixers: A collection of SOTA efficient token/channel mixers
  ☆11Updated 4 months ago
• fmfi-compbio / admm-pruning
  ☆23Updated 7 months ago
• smonsays / hypernetwork-attention
  Official code for the paper "Attention as a Hypernetwork"
  ☆25Updated 8 months ago
• sanagno / adaptively_sparse_attention
  ☆20Updated last year
• OpenGVLab / LLMPrune-BESA
  BESA is a differentiable weight pruning technique for large language models.
  ☆14Updated last year
• sustcsonglin / mamba-triton
  ☆47Updated last year
• RAIVNLab / MatFormer-OLMo
  Code repository for the public reproduction of the language modelling experiments on "MatFormer: Nested Transformer for Elastic Inference…
  ☆19Updated last year
• OpenNLPLab / HGRN2
  HGRN2: Gated Linear RNNs with State Expansion
  ☆53Updated 7 months ago
• VITA-Group / Junk_DNA_Hypothesis
  [ICML 2024] Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity; Lu Yin*, Ajay Jaiswal*, Shiwei Liu, So…
  ☆16Updated 9 months ago
• HazyResearch / prefix-linear-attention
  ☆52Updated 8 months ago
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆58Updated 4 months ago
• glassroom / heinsen_attention
  Reference implementation of "Softmax Attention with Constant Cost per Token" (Heinsen, 2024)
  ☆24Updated 9 months ago
• ldery / Bonsai
  Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"
  ☆27Updated 11 months ago
• IST-DASLab / RoSA
  Official implementation of the ICML 2024 paper RoSA (Robust Adaptation)
  ☆39Updated last year
• andyjm3 / SLTrain
  SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining (NeurIPS 2024)
  ☆30Updated 4 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
• sjelassi / transformers_ssm_copy
  ☆30Updated last year
• kyegomez / Blockwise-Parallel-Transformer
  32 times longer context window than vanilla Transformers and up to 4 times longer than memory efficient Transformers.
  ☆46Updated last year
• wjxts / RegularizedBN
  ☆21Updated 2 years ago
• shoaibahmed / llm_depth_pruning
  Official implementation of the paper: "A deeper look at depth pruning of LLMs"
  ☆14Updated 7 months ago
• 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…
  ☆48Updated 2 years ago
• VITA-Group / instant_soup
  [ICML2023] Instant Soup Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models. Ajay Jaiswal, Shiwei Liu, Ti…
  ☆11Updated last year
• 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
• ziplab / QLLM
  [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…
  ☆26Updated last year
• imagination-research / LCSC
  [ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
  ☆14Updated last month
• prateeky2806 / ComPEFT
  ☆25Updated last year