Yolov5_DeepSort_Pytorch - Real-time multi-object tracker using YOLO v5 and deep sort https://t.co/zEFH2l4uuL
— Python Trending (@pythontrending) July 11, 2021
Yolov5_DeepSort_Pytorch - Real-time multi-object tracker using YOLO v5 and deep sort https://t.co/zEFH2l4uuL
— Python Trending (@pythontrending) July 11, 2021
This tutorial will introduce compute and data-efficient transformers and provide a step-by-step to create your own Vision Transformers. Through this guide, you'll be able to train state of the art results for classification in both computer vision & NLP. https://t.co/d3bc7ijeBJ
— PyTorch (@PyTorch) June 28, 2021
It’s never been easier to deploy a state-of-the-art ML model to a phone. In this blog, we’ll provide a quick overview of PyTorch Mobile-powered demo apps running various state-of-the-art PyTorch 1.9 ML models spanning images, video, audio and text.https://t.co/RxNNnktYvr
— PyTorch (@PyTorch) June 18, 2021
Want to run your PyTorch training loop on multi-GPUs or TPUs without using an abstract class you can't control or tweak easily? Try out 🤗 Accelerate! https://t.co/12l2JYZL0w
— Sylvain Gugger (@GuggerSylvain) April 16, 2021
pytorchvideo: A deep learning library for video understanding research
— AK (@ak92501) April 15, 2021
github: https://t.co/oXc1YiASd4
Using PyTorch + NumPy? A bug that plagues thousands of open-source ML projects https://t.co/piVdQidmZH
— Andrej Karpathy (@karpathy) April 11, 2021
hah yes, a favorite super common super subtle bug 🐛. Bugs in deep learning silently make results slightly worse, pays to be v distrusting & defensive: https://t.co/5lBy4J77aS
RepVGG: Making VGG-style ConvNets Great Again
— Andrej Karpathy (@karpathy) April 11, 2021
paper: https://t.co/Y5WfgvqxHO
PyTorch code: https://t.co/ydk0RUf6JU
👌Spells out the benefits of very simple/uniform/fast (latency, not FLOPS) deployment architectures. A lot of complexity often due to optimization, not architecture. pic.twitter.com/8GliE4JDiq
Introducing torch.profiler! New PyTorch Profiler collects both GPU and framework related info, correlates them, performs automatic detection of bottlenecks in the model, generates recommendations on how to resolve these bottlenecks, and visualize.
— PyTorch (@PyTorch) March 25, 2021
Read 👉https://t.co/Ottly5CtF4 pic.twitter.com/zkFCts1lzn
Fast, differentiable sorting and ranking in PyTorch https://t.co/xaLlhOaejy #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) March 22, 2021
Avalanche: End-to-End Library for Continual Learning based on PyTorch
— ML Review (@ml_review) March 19, 2021
By @ContinualAI
Covers:
– Benchmarks
– Training
– Evaluation
– Models
Project: https://t.co/rZr2x2a7OE
GitHub: https://t.co/WzHDV632Rv pic.twitter.com/FBRmEsupDC
⚠️ New in the v0.0.7 release of `huggingface_hub` ⚠️
— Julien Chaumond (@julien_c) March 18, 2021
Community member @7vasudevgupta added the ability to mix-in a class named ModelHubMixin to *any PyTorch model* to be able to save, upload it, and load it from the https://t.co/ZygXVJ8qCM hub:
🔥🔥https://t.co/1jZ4Y6GPwo pic.twitter.com/mfCwH0f5sF
ConSelfSTransDRLIB: Contrastive Self-supervised Transformers for Disentangled Representation Learning with Inductive Biases is All you need, and where to find them.
— Sebastian Raschka (@rasbt) March 13, 2021
The current state of deep learning research summarized in one sentence.
(Credit: https://t.co/RTuht7Lkj0)