fla-org / flame
🔥 A minimal training framework for scaling FLA models
☆82Updated this week
Alternatives and similar repositories for flame:
Users that are interested in flame are comparing it to the libraries listed below
- ☆116Updated last month
- [ICLR 2025] COAT: Compressing Optimizer States and Activation for Memory-Efficient FP8 Training☆164Updated last month
- Triton-based implementation of Sparse Mixture of Experts.☆207Updated 3 months ago
- [ICLR2025] Codebase for "ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing", built on Megatron-LM.☆65Updated 3 months ago
- A sparse attention kernel supporting mix sparse patterns☆164Updated last month
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆158Updated 8 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆73Updated 4 months ago
- An unofficial implementation of "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆34Updated 9 months ago
- Triton implementation of FlashAttention2 that adds Custom Masks.☆102Updated 7 months ago
- 16-fold memory access reduction with nearly no loss☆81Updated this week
- ☆101Updated last year
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆59Updated 4 months ago
- Official repository for LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers☆207Updated 7 months ago
- [ICLR 2024 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆74Updated 9 months ago
- Low-bit optimizers for PyTorch☆125Updated last year
- Here we will test various linear attention designs.☆60Updated 10 months ago
- ☆87Updated 5 months ago
- Odysseus: Playground of LLM Sequence Parallelism☆66Updated 9 months ago
- Homepage for ProLong (Princeton long-context language models) and paper "How to Train Long-Context Language Models (Effectively)"☆163Updated 2 weeks ago
- Linear Attention Sequence Parallelism (LASP)☆79Updated 9 months ago
- [NeurIPS-2024] 📈 Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies https://arxiv.org/abs/2407.13623☆80Updated 5 months ago
- Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"☆153Updated 9 months ago
- Fast and memory-efficient exact attention☆67Updated 2 weeks ago
- Stick-breaking attention☆48Updated last week