#pytorch 搜尋結果
❄️ We’re excited to welcome @Snowflake as a Premier Member of the PyTorch Foundation 🎉 Snowflake’s AI Research Team is advancing open source AI with #PyTorch, from inference optimizations to training breakthroughs. 👉 Read the announcement: hubs.la/Q03MyQ_h0
Zmierzyłem to. Aktywność neuronów w moim modelu BDH niemal się podwoiła, gdy przerwałem nudny, powtarzalny wzorzec. To dowód na dynamiczną alokację zasobów, podobną do uwagi w systemach biologicznych :) github.com/takzen/BDH-Off… #AI #PyTorch #MachineLearning #PathwayAI
Discover the tools shaping the #PyTorch ecosystem! At #PyTorchCon (Oct 22-23, San Francisco), dive into updates on vLLM, Deepspeed, Huggingface, Lightning, & more. ⚡ Explore the track: hubs.ly/Q03JcdFh0 Register: hubs.ly/Q03Jcbhj0
📚 From classrooms to cutting-edge labs, #PyTorch is fueling discovery. At #PyTorchCon (Oct 22–23, SF), explore the PyTorch in Academia Track and see how it drives research and education. 🔗 hubs.ly/Q03KbTRS0 🎟 hubs.ly/Q03KbTTM0
Zainspirowany oficjalnym kodem AI "Dragon Hatchling", udostępnionym dzisiaj przez Pathway, od razu wziąłem go na warsztat! :) Wytrenowałem 25M model, żeby sprawdzić go dokładniej. Wyniki są obiecujące :) github.com/takzen/BDH-Off… #AI #PyTorch #MachineLearning #PathwayAI
🏭 From prototypes to production, #PyTorch is powering business innovation. At #PyTorchCon (Oct 22–23, SF), dive into the PyTorch in Industry Track for real-world use cases and success stories. 🔗 hubs.la/Q03KHNM60 🎟 hubs.la/Q03KHHjM0
Disaggregated Inference at Scale with #PyTorch & #vLLM: Meta’s vLLM disagg implementation improves inference efficiency in latency & throughput vs its internal stack, with optimizations now being upstreamed to the vLLM community. 🔗 hubs.la/Q03J87tS0
Go big with the #PyTorch at Scale Track at #PyTorchCon, Oct 22-23 in San Francisco. 🚀 Learn how to build, train, and serve models at massive scale with distributed training, parallelism, and production-ready #AI. 🔗 hubs.la/Q03JsltP0 🎟 hubs.la/Q03JsrY00
Here's how to load an ONNX model in Clojure: (onnx "my-model-file.onnx") That's it. From then on, it completely automatically fits in the existing Tensor infrastructure an can be run in many different ways, with more or less custom configuration! github.com/uncomplicate/d… #PyTorch
Disaggregated Inference at Scale with #PyTorch & #vLLM: Meta’s vLLM disagg implementation improves inference efficiency in latency & throughput vs its internal stack, with optimizations now being upstreamed to the vLLM community. 🔗 hubs.la/Q03J87tS0
FlashAttention in 3D? Our latest blog explores the #kernel design of 2-Simplicial #Attention, modeling the algorithm with a hardware aligned design and rewriting the entire kernel in TLX (Triton Low Level Extensions). 🔗 hubs.la/Q03H6S9D0 #PyTorch #OpenSourceAI
2nd Edition, 746 pages, massive! ⬇️ Modern #ComputerVision with #PyTorch #DeepLearning — from practical fundamentals to advanced applications and #GenerativeAI: amzn.to/3xAkB7X v/ @PacktDataML —— #DataScience #MachineLearning #AI #ML #GenAI #DataScientist —— 𝓚𝓮𝔂…
Have you heard the news? MLflow now supports tracking for @DSPyOSS optimization workflows—just like it does for #PyTorch training! With DSPy, you can automatically optimize your #LLM prompts using powerful optimizers, and now #MLflow is the first and only framework to bring full…
Build fast, responsive speech apps on AI PCs. This expert-level workshop shows how to use #PyTorch and #GPU acceleration to power speech recognition and synthesis with transformer-based models. May 29 at 9am PST. Register now: intel.ly/4jeUtkU
Zmierzyłem to. Aktywność neuronów w moim modelu BDH niemal się podwoiła, gdy przerwałem nudny, powtarzalny wzorzec. To dowód na dynamiczną alokację zasobów, podobną do uwagi w systemach biologicznych :) github.com/takzen/BDH-Off… #AI #PyTorch #MachineLearning #PathwayAI
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