CUDA

  1. Flash Linear Attention: Efficient Attention Mechanisms for Transformers

    The transformer architecture has been the dominant model for sequence processing since its introduction, but it carries a fundamental limitation: the...

    AI
  2. Causal-Conv1d: The CUDA-Optimized Kernel Powering Mamba State Space Models

    The Transformer architecture has dominated deep learning for years, but a new challenger has emerged: state space models (SSMs). At the heart of one...

    AI
  3. bitsandbytes: Essential k-bit Quantization Library for LLM Training and Inference

    Large language models have grown far beyond the memory capacity of consumer hardware. A 70-billion-parameter model requires 140 gigabytes of GPU...

    AI