Zhiqiang Wang @_zhiq

👿 zhiqwang.com Beijing Joined July 2016

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First Issues Bot @first_issues

3 years ago

[docs] yolort and yolov5 version matching problem github.com/zhiqwang/yolov… #github #JavaScript #Shell #Python #C++ #CMake

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Python Trending 🇺🇦 @pythontrending

3 years ago

yolov5-rt-stack - yolort is a runtime stack for yolov5 on specialized accelerators such as libtorch, onnxruntime, tensorrt, tvm and ncnn. github.com/zhiqwang/yolov…

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PyTorch @PyTorch

3 years ago

We’re excited to announce support for GPU-accelerated PyTorch training on Mac! Now you can take advantage of Apple silicon GPUs to perform ML workflows like prototyping and fine-tuning. Learn more: pytorch.org/blog/introduci…

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PyTorch @PyTorch

3 years ago

The Intel engineers in the PyTorch open-source community have created an new Intel® Extension for PyTorch* which maximizes deep learning inference and training performance on Intel CPUs. Get the extension to make use of these features today: @fanzhao_intel bit.ly/3wChKHg

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Vasilis Vryniotis @bbriniotis

3 years ago

TorchVision refreshed its most popular Detection & Segmentation models to improve their accuracies: - RetinaNet: 41.5 mAP (+5.1) - FasterRCNN: 46.7 mAP (+9.7) - MaskRCNN: 47.4 box mAP (+9.5) / 41.8 mask mAP (+7.2) github.com/pytorch/vision… #MachineLearning #ComputerVision #PyTorch

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Vasilis Vryniotis @bbriniotis

4 years ago

We just merged FCOS, the object detection architecture, along with pre-trained weights in TorchVision: github.com/pytorch/vision… Massive thanks to Hu Ye, @zhiq_w and Joao Gomes for their work on fully reproducing the results of the paper: arxiv.org/abs/1904.01355 (1/3)

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Vasilis Vryniotis @bbriniotis

4 years ago

Say hello to TorchVision's new Multi-weight support API!! It's fully-BC, enables support of multiple pre-trained weights for the same model variant, bundles together the preprocessing transforms & other crucial meta-data: github.com/pytorch/vision… #MachineLearning #ComputerVision

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Edward Z. Yang @ezyang

4 years ago

I just realized notebooks are literally literate programming but with outputs too 😂

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PyTorch @PyTorch

4 years ago

New PyTorch domain library updates! - TorchRec in beta - TorchAudio adds Enformer- and RNN-T-based models/recipes - TorchText supports RoBERTa and XLM-R models - TorchVision adds 4 model families and 14 classification datasets Learn more👇 pytorch.org/blog/pytorch-1…

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Aniket @aniketmaurya

4 years ago

YoloRT is a runtime stack for yolov5 on specialized accelerators such as libtorch, @onnxruntime, tensorrt, TVM and ncnn. 👉 GitHub repo: buff.ly/34IJYGk #MachineLearning #DeepLearning #DataScience #MLOps

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Sasha Rush @srush_nlp

4 years ago

Torch Golf #3 🔥⛳️ Beam Search applied to Traveling Salesman.

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nihui @nihui

4 years ago

brew install ncnn

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nihui @nihui

4 years ago

PNNX is an open standard for PyTorch model interoperability github.com/nihui/ncnn/tre… github.com/Tencent/ncnn/p…

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Francisco Massa @fvsmassa

4 years ago

This is a very nice new feature in torchvision contributed by Alexander (which will be present in the next release in a couple of weeks). If you were looking into extracting intermediate activations from an arbitrary model in a generic way, check this out!

Alexander Soare @asoare159

4 years ago

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Alexander Soare @asoare159

4 years ago

Had a blast putting together one of TorchVision's newest utilities: feature extraction via a graph representation of your model. Check it out on the main branch: pytorch.org/vision/main/fe… Many thanks @fvsmassa and colleagues for the support! #PyTorch #ComputerVision @DeepLearning

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消极 @cxiaoji

6 years ago

我七岁拜过一个大师学画画。那时大师说哪个孩子有灵气，全家天都亮了；说谁不适合学艺术，五雷轰顶。有一天我意识到大师的赞美和家长交的钱成正比，愤然退学改去上数学班。数学会做就是会做，不需要高高在上的成年人来告诉我。如今每听到秃顶大叔说小姑娘「不适合学编程」，我总暗自惋惜他们入错了行。

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PyTorch Best Practices @PyTorchPractice

6 years ago

PyTorch implementation of text recognition based on Fairseq github.com/zhiqwang/image… #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch

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Edward Z. Yang @ezyang

6 years ago

Annotated slides in essay form of my "PyTorch Internals" talk are now up at blog.ezyang.com/2019/05/pytorc…

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Ilya Sutskever @ilyasut

7 years ago

Studying math must be so much easier now that ML is popular. Derivatives, high-d spaces, probability, statistics, and eigenvectors all become alive in ML. Beats computing planetary motion.