lucidrains / mixture-of-expertsLinks
A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models
☆776Updated last year
Alternatives and similar repositories for mixture-of-experts
Users that are interested in mixture-of-experts are comparing it to the libraries listed below
Sorting:
- PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538☆1,134Updated last year
- Implementation of ST-Moe, the latest incarnation of MoE after years of research at Brain, in Pytorch☆345Updated last year
- ☆654Updated 3 weeks ago
- Transformer based on a variant of attention that is linear complexity in respect to sequence length☆784Updated last year
- Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch☆708Updated last week
- A curated reading list of research in Mixture-of-Experts(MoE).☆638Updated 8 months ago
- Tutel MoE: Optimized Mixture-of-Experts Library, Support DeepSeek FP8/FP4☆851Updated this week
- A collection of AWESOME things about mixture-of-experts☆1,159Updated 7 months ago
- A fast MoE impl for PyTorch☆1,757Updated 5 months ago
- Code for the ALiBi method for transformer language models (ICLR 2022)☆536Updated last year
- Implementation of Linformer for Pytorch☆290Updated last year
- Implementation of the Transformer variant proposed in "Transformer Quality in Linear Time"☆366Updated last year
- An implementation of local windowed attention for language modeling☆460Updated 6 months ago
- Rotary Transformer☆979Updated 3 years ago
- Long Range Arena for Benchmarking Efficient Transformers☆759Updated last year
- Implementation of Soft MoE, proposed by Brain's Vision team, in Pytorch☆304Updated 3 months ago
- Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time☆474Updated last year
- Implementation of 💍 Ring Attention, from Liu et al. at Berkeley AI, in Pytorch☆529Updated 2 months ago
- TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.☆1,625Updated last week
- Large Context Attention☆718Updated 5 months ago
- Pytorch library for fast transformer implementations☆1,724Updated 2 years ago
- (Unofficial) PyTorch implementation of grouped-query attention (GQA) from "GQA: Training Generalized Multi-Query Transformer Models from …☆171Updated last year
- ☆292Updated 7 months ago
- Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States☆1,227Updated last year
- AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning (ICLR 2023).☆336Updated 2 years ago
- maximal update parametrization (µP)☆1,554Updated 11 months ago
- [ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation☆811Updated 9 months ago
- [ICLR2025 Spotlight🔥] Official Implementation of TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters☆563Updated 5 months ago
- Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"☆379Updated last year
- Implementation of Recurrent Memory Transformer, Neurips 2022 paper, in Pytorch☆410Updated 6 months ago