flash-linear-attention vs transformers
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| flash-linear-attention | transformers | |
|---|---|---|
| Tagline | Efficient implementations for emerging model architectures | 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models |
| Stars | 5.3k | 162k |
| Forks | 571 | 34k |
| Open issues | 67 | 2.5k |
| Language | Python | Python |
| License | MIT | Apache-2.0 |
| Last pushed | Jul 7, 2026 | Jul 7, 2026 |
| Categories | LLM Frameworks | Data & Retrieval, Model Training, LLM Frameworks |
flash-linear-attention
Flash Linear Attention provides hardware-efficient building blocks, training-ready layers, and components for modern sequence models, supporting various attention mechanisms and hybrid LLM architectures.
Python
transformers
Repo hosts a Python library and framework for NLP, text, audio, vision, multimodal AI model creation, training and inference using PyTorch.
Python