Alternatives and similar repositories for awesome-early-exiting

Users that are interested in awesome-early-exiting are comparing it to the libraries listed below

• QingruZhang / PLATON
  This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).
  ☆46Updated 3 years ago
• princeton-nlp / CoFiPruning
  [ACL 2022] Structured Pruning Learns Compact and Accurate Models https://arxiv.org/abs/2204.00408
  ☆198Updated 2 years ago
• kssteven418 / LTP
  [KDD'22] Learned Token Pruning for Transformers
  ☆102Updated 2 years ago
• WoosukKwon / retraining-free-pruning
  [NeurIPS 2022] A Fast Post-Training Pruning Framework for Transformers
  ☆192Updated 2 years ago
• falcon-xu / early-exit-papers
  A curated list of early exiting (LLM, CV, NLP, etc)
  ☆69Updated last year
• SimiaoZuo / MoEBERT
  This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022).
  ☆113Updated 3 years ago
• thunlp / MoEfication
  ☆142Updated last year
• yxli2123 / LoSparse
  ☆62Updated 2 years ago
• huggingface / block_movement_pruning
  Block Sparse movement pruning
  ☆81Updated 5 years ago
• raymin0223 / fast_robust_early_exit
  Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding (EMNLP 2023 Long)
  ☆65Updated last year
• RunxinXu / ContrastivePruning
  Source code for our AAAI'22 paper 《From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression》
  ☆25Updated 4 years ago
• microsoft / Stochastic-Mixture-of-Experts
  This package implements THOR: Transformer with Stochastic Experts.
  ☆65Updated 4 years ago
• dguo98 / DiffPruning
  Parameter Efficient Transfer Learning with Diff Pruning
  ☆74Updated 4 years ago
• kssteven418 / BigLittleDecoder
  [NeurIPS'23] Speculative Decoding with Big Little Decoder
  ☆95Updated last year
• TobiasLee / Awesome-Efficient-PLM
  Must-read papers on improving efficiency for pre-trained language models.
  ☆105Updated 3 years ago
• huawei-noah / Efficient-NLP
  ☆95Updated last year
• asappresearch / flop
  Pytorch library for factorized L0-based pruning.
  ☆45Updated 2 years ago
• cambridgeltl / autopeft
  AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning (Zhou et al.; TACL 2024)
  ☆50Updated last year
• CASIA-LMC-Lab / FLAP
  [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
  ☆65Updated last year
• benzakenelad / BitFit
  Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models
  ☆143Updated 3 years ago
• teelinsan / parallel-decoding
  Repository of the paper "Accelerating Transformer Inference for Translation via Parallel Decoding"
  ☆121Updated 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…
  ☆56Updated 2 years ago
• Hunter-DDM / stablemoe
  Code for the ACL-2022 paper "StableMoE: Stable Routing Strategy for Mixture of Experts"
  ☆51Updated 3 years ago
• varunnair18 / FISH
  Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
  ☆59Updated 3 years ago
• hdong920 / LESS
  ☆53Updated last year
• txsun1997 / Black-Box-Tuning
  ICML'2022: Black-Box Tuning for Language-Model-as-a-Service & EMNLP'2022: BBTv2: Towards a Gradient-Free Future with Large Language Model…
  ☆273Updated 3 years ago
• castorini / DeeBERT
  DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
  ☆161Updated 3 years ago
• princeton-nlp / LM-Kernel-FT
  A Kernel-Based View of Language Model Fine-Tuning https://arxiv.org/abs/2210.05643
  ☆78Updated 2 years ago
• VITA-Group / BERT-Tickets
  [NeurIPS 2020] "The Lottery Ticket Hypothesis for Pre-trained BERT Networks", Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Ya…
  ☆141Updated 3 years ago
• rycolab / differentiable-subset-pruning
  ☆16Updated 4 years ago