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@PyTorch

PyTorch

@PyTorch
Tensors and neural networks in Python with strong hardware acceleration. PyTorch is an open source project at the Linux Foundation. #PyTorchFoundation
pytorch.org
Joined September 2016
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  • @PyTorch
    PyTorch
    @PyTorch
    24m
    🚨 Final call, AI community! Ticket prices for #PyTorchCon North America go up TONIGHT at 11:59 PM PDT. Save $200 and join AI pioneers, researchers, and developers October 20-21 in San Jose. Hurry & get your pass now: bit.ly/4sh3DSw
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  • @PyTorch
    PyTorch
    @PyTorch
    16h
    The PyTorch AOTI backend delivered a 1.14x–1.28x speedup over the Python backend in NVIDIA’s HSTU inference tests when deployed with Triton Inference Server. With the PyTorch AOTI backend and KV cache, @nvidia reports a 2.20x–2.38x speedup in an ideal all-GPU cache-hit scenario.
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    How Generative Recommenders Are Redefining RecSys at Scale | NVIDIA Technical Blog
    From developer.nvidia.com
    2
  • @PyTorch
    PyTorch
    @PyTorch
    17h
    TorchSpec is a PyTorch-native framework for training speculative decoding draft models. This release, a collaboration with @vllm_project, shows it in action on Kimi K3 @lightseekorg
    @lightseekorg
    LightSeek Foundation
    @lightseekorg
    Sep 3
    Releasing the @Kimi_Moonshot K3 Draft Collection — 3 draft models (EAGLE-3, DFlash2, DSpark) trained with TorchSpec and @vllm_project on @NVIDIAAI GB200. 🚀 We also shared the data recipes. More on the blog → lightseek.org/blog/kimi-k3-d…
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    4
  • @PyTorch
    PyTorch
    @PyTorch
    17h
    In PyTorch 2.14, fault tolerance becomes a first-class c10d concept, with in-place process-group reconfiguration. When a rank fails in a large job, the usual recovery is to tear down the process group and restart, which discards warm state across the whole cluster. Backend and
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  • @PyTorch
    PyTorch
    @PyTorch
    21h
    At PyTorch Conference North America 2026, hear directly from and connect with the people working on PyTorch, @vllm_project, @DeepSpeedAI, @raydistributed, Helion, and Safetensors, alongside experts working across the AI stack. At #PyTorchCon NA 2025, @richliaw (@raydistributed,
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