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ffpa-attn: Fast and Memory-Efficient Exact Attention (BF16/FP16/FP8/FP4) for Large Headdim, 1.5x~15x🔥🔥 speedup over standard PyTorch SDPA.
Fast and Memory-Efficient Exact Attention (BF16/FP16/FP8/FP4) for Large Headdim, 1.5x~15x speedup over PyTorch SDPA.
A lite C++ AI toolkit: 100+ models with MNN, ORT and TRT, including Det, Seg, Stable-Diffusion, Face-Fusion.
Modern CUDA Learn Notes with PyTorch for Beginners, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.
🚀 Efficient implementations for emerging model architectures
通过集成国内主流原生大模型提供商,为开发者提供更加丰富、更适合本土需求的 AI 编程助手选择。 目前已内置支持 智谱AI、MiniMax、MoonshotAI、DeepSeek、阿里云百炼、快手万擎、火山方舟、腾讯云、Xiaomi MiMo 等原生大模型提供商。 此外,扩展插件已适配支持 OpenAI 与 Anthropic 的 API 接口兼容模型,支持自定义接入任何提供兼容接口的第三方云服务模型。
SGLang is a fast serving framework for large language models and vision language models.
📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
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