Alternatives and similar repositories for MoLE

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

• lliai / D2MoE
  D^2-MoE: Delta Decompression for MoE-based LLMs Compression
  ☆72Updated 10 months ago
• mdy666 / Qwen-Native-Sparse-Attention
  qwen-nsa
  ☆87Updated 3 months ago
• LINs-lab / DynMoE
  [ICLR 2025] Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
  ☆153Updated 7 months ago
• pprp / Awesome-Efficient-MoE
  Efficient Mixture of Experts for LLM Paper List
  ☆166Updated 4 months ago
• thu-nics / R2R
  [NeurIPS'25] The official code implementation for paper "R2R: Efficiently Navigating Divergent Reasoning Paths with Small-Large Model Tok…
  ☆76Updated last week
• htqin / IR-QLoRA
  [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…
  ☆67Updated last year
• maomaocun / dLLM-cache
  Official PyTorch implementation of the paper "dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching" (dLLM-Cache…
  ☆197Updated 2 months ago
• OpenSparseLLMs / Linearization
  ☆66Updated 7 months ago
• mit-han-lab / x-attention
  [ICML 2025] XAttention: Block Sparse Attention with Antidiagonal Scoring
  ☆269Updated 7 months ago
• ruikangliu / Quantized-Reasoning-Models
  [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"
  ☆67Updated 7 months ago
• OpenMOSS / DiRL
  ☆145Updated 3 weeks ago
• fla-org / flash-bidirectional-linear-attention
  Triton implement of bi-directional (non-causal) linear attention
  ☆65Updated last week
• ThisisBillhe / ZipCache
  [NeurIPS 2024] The official implementation of ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification
  ☆32Updated 10 months ago
• OpenSparseLLMs / Linear-MoE
  ☆129Updated 8 months ago
• sramshetty / mixture-of-depths
  An unofficial implementation of "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"
  ☆36Updated last year
• XiaomiMiMo / lmms-eval
  Accelerating the development of large multimodal models (LMMs) with one-click evaluation module - lmms-eval.
  ☆71Updated 6 months ago
• pprp / Pruner-Zero
  [ICML24] Pruner-Zero: Evolving Symbolic Pruning Metric from scratch for LLMs
  ☆98Updated last year
• horseee / dKV-Cache
  [NeurIPS'25] dKV-Cache: The Cache for Diffusion Language Models
  ☆129Updated 8 months ago
• thu-ml / ReMoE
  [ICLR2025] Codebase for "ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing", built on Megatron-LM.
  ☆105Updated last year
• thu-nics / MBQ
  The code repository of "MBQ: Modality-Balanced Quantization for Large Vision-Language Models"
  ☆75Updated 10 months ago
• JarvisPei / CMoE
  Implementation for the paper: CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference
  ☆34Updated 11 months ago
• kyegomez / Mixture-of-Depths
  Implementation of the paper: "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"
  ☆114Updated this week
• inclusionAI / dFactory
  Easy and Efficient dLLM Fine-Tuning
  ☆209Updated 3 weeks ago
• mdy666 / Scalable-Flash-Native-Sparse-Attention
  ☆48Updated last month
• MIRALab-USTC / LLM-AttentionPredictor
  The code for "AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference", Qingyue Yang, Jie Wang, Xing Li, Zhihai Wang, Ch…
  ☆27Updated 6 months ago
• BICLab / MetaLA
  Offical implementation of "MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map" (NeurIPS2024 Oral)
  ☆34Updated last year
• wutaiqiang / MoSLoRA
  ☆125Updated last year
• OpenSparseLLMs / MoM
  ☆120Updated last week
• OpenSparseLLMs / LLaMA-MoE-v2
  🚀 LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training
  ☆91Updated last year
• thu-nics / MoA
  [CoLM'25] The official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>
  ☆155Updated 3 weeks ago