acosharma / elita-transformer
Official Repository for Efficient Linear-Time Attention Transformers.
☆18Updated 5 months ago
Related projects ⓘ
Alternatives and complementary repositories for elita-transformer
- ☆11Updated last year
- Engineering the state of RNN language models (Mamba, RWKV, etc.)☆32Updated 5 months ago
- ☆31Updated 10 months ago
- Efficient PScan implementation in PyTorch☆15Updated 10 months ago
- [NeurIPS 2023] Sparse Modular Activation for Efficient Sequence Modeling☆35Updated 11 months ago
- BigKnow2022: Bringing Language Models Up to Speed☆14Updated last year
- ☆18Updated 5 months ago
- Fine-Tuning Pre-trained Transformers into Decaying Fast Weights☆19Updated 2 years ago
- Reference implementation of "Softmax Attention with Constant Cost per Token" (Heinsen, 2024)☆24Updated 5 months ago
- Blog post☆16Updated 9 months ago
- sigma-MoE layer☆18Updated 10 months ago
- Triton Implementation of HyperAttention Algorithm☆46Updated 11 months ago
- Source-to-Source Debuggable Derivatives in Pure Python☆14Updated 9 months ago
- A large-scale RWKV v6 inference with FLA . Capable of inference by combining multiple states(Pseudo MoE). Easy to deploy on docker. Suppo…☆16Updated last week
- Official code for the paper "Attention as a Hypernetwork"☆23Updated 4 months ago
- Code for the paper "Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns"☆16Updated 8 months ago
- ☆21Updated last month
- ☆18Updated last month
- RWKV model implementation☆38Updated last year
- ☆45Updated 9 months ago
- GoldFinch and other hybrid transformer components☆39Updated 4 months ago
- ☆24Updated 8 months ago
- ☆45Updated 4 months ago
- Parallel Associative Scan for Language Models☆18Updated 10 months ago
- ☆29Updated 2 years ago
- My explorations into editing the knowledge and memories of an attention network☆34Updated last year
- Here we will test various linear attention designs.☆56Updated 6 months ago
- Efficient Scaling laws and collaborative pretraining.☆13Updated this week
- Official repository for the paper "Approximating Two-Layer Feedforward Networks for Efficient Transformers"☆36Updated last year