Alternatives and similar repositories for Random-MoE-as-Dropout

Users that are interested in Random-MoE-as-Dropout are comparing it to the libraries listed below

• Leooyii / LCEG
  Long Context Extension and Generalization in LLMs
  ☆62Updated last year
• Shwai-He / MEO
  The source code of "Merging Experts into One: Improving Computational Efficiency of Mixture of Experts (EMNLP 2023)":
  ☆44Updated last year
• thunlp / MoEfication
  ☆143Updated last year
• r-three / smear
  ☆30Updated 2 years ago
• BaohaoLiao / mefts
  [NeurIPS 2023] Make Your Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning
  ☆33Updated 2 years ago
• kamanphoebe / Look-into-MoEs
  [NAACL 2025] A Closer Look into Mixture-of-Experts in Large Language Models
  ☆58Updated 11 months ago
• song-wx / SIFT
  [ICML2024 Spotlight] Fine-Tuning Pre-trained Large Language Models Sparsely
  ☆24Updated last year
• gregorbachmann / Next-Token-Failures
  ☆108Updated last year
• DAMO-NLP-SG / CLEX
  [ICLR 2024] CLEX: Continuous Length Extrapolation for Large Language Models
  ☆78Updated last year
• PKU-ML / LongPPL
  Code for ICLR 2025 Paper "What is Wrong with Perplexity for Long-context Language Modeling?"
  ☆110Updated 3 months ago
• thu-coai / MiniPLM
  [ICLR 2025] MiniPLM: Knowledge Distillation for Pre-Training Language Models
  ☆71Updated last year
• allenai / hyper-task-descriptions
  Learning adapter weights from task descriptions
  ☆19Updated 2 years ago
• DRSY / KV_Compression
  [EMNLP 2023]Context Compression for Auto-regressive Transformers with Sentinel Tokens
  ☆25Updated 2 years ago
• sail-sg / scaling-with-vocab
  [NeurIPS-2024] 📈 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies https://arxiv.org/abs/2407.13623
  ☆89Updated last year
• 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
• ChaosCodes / ProPETL
  One Network, Many Masks: Towards More Parameter-Efficient Transfer Learning
  ☆40Updated 2 years ago
• chijames / KERPLE
  ☆20Updated 3 years ago
• princeton-nlp / Edge-Pruning
  [NeurIPS 2024 Spotlight] Code and data for the paper "Finding Transformer Circuits with Edge Pruning".
  ☆64Updated 5 months ago
• shaochenze / PatchTrain
  Code for paper "Patch-Level Training for Large Language Models"
  ☆97Updated 2 months ago
• ldery / Bonsai
  Code for "Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes"
  ☆30Updated last year
• abdelfattah-lab / TokenButler
  ☆27Updated 2 months ago
• qiuzh20 / EMoE
  Official PyTorch Implementation of EMoE: Unlocking Emergent Modularity in Large Language Models [main conference @ NAACL2024]
  ☆39Updated last year
• yule-BUAA / MergeLLM
  Codes for Merging Large Language Models
  ☆35Updated last year
• chuanyang-Zheng / DAPE
  The this is the official implementation of "DAPE: Data-Adaptive Positional Encoding for Length Extrapolation"
  ☆41Updated last year
• john-hewitt / implicit-ins
  Codebase for Instruction Following without Instruction Tuning
  ☆36Updated last year
• hamishivi / automated-instruction-selection
  Exploration of automated dataset selection approaches at large scales.
  ☆52Updated 11 months ago
• locuslab / scaling_laws_data_filtering
  ☆64Updated last year
• QingruZhang / PLATON
  This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).
  ☆46Updated 3 years ago
• facebookresearch / RLCD
  Reproduction of "RLCD Reinforcement Learning from Contrast Distillation for Language Model Alignment
  ☆69Updated 2 years ago
• TianduoWang / DPO-ST
  [ACL 2024] Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning
  ☆53Updated last year