Technology · Framework

PyTorch

Framework · Meta · Catalog tech@1

Deep learning framework.

Matched as
  • pytorch
  • torch

Momentum

Each signal is ranked as a percentile among the technologies that have it. A signal without enough history is not counted, and never shown as zero. How momentum works

Momentum

Collecting0 of 5 signals

No score yet. Momentum is published only when at least 2 of the 5 signals have history. PyTorch has 0, so there is no single number: each signal is shown on its own below. It is not a zero, and nothing is estimated in its place.

Snapshot OCT 24, 2026 · Scoring tech@1

Official repository stars
Collecting
Star growth needs repository snapshots 30 days apart.103,616 stars now
Member repository stars
Collecting
Star growth needs repository snapshots 30 days apart.0 new members in 30 days
Package adoption
Not published by its registries
Its packages’ registries publish no adoption figure, so there is nothing to grow.
Open models
No official models
No official model on Hugging Face, so this signal does not apply.
News
Collecting
News counts once there are 3 events across the last 60 days; it has 2.2 in the last 30 days · 0 in the 30 before

Adoption by registry

The growth of PyTorch’s own packages, one row per registry in that registry’s own unit. Registries count different things over different windows, so they are never added together.

No registry has two observations of PyTorch’s own packages about 30 days apart yet, so there is no growth to show. Nothing is estimated in its place.

News activity

Events · 7 days
2published events that mention it
Events · 30 days
2published events that mention it
Previous 30 days
0events in the 30 days before

Momentum history

Momentum history starts OCT 8, 2026. A chart appears once two daily snapshots carry a score; none does so far.

Repositories

Official 1

  • pytorch/pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Official repositoryPython

    103.6K stars

Members 794repositories tagged with one of its aliases, most-starred first

  • qubvel/ttach

    Image Test Time Augmentation with PyTorch!

    Tagged pytorchPython

    1K stars

  • ClementPinard/SfmLearner-Pytorch

    Pytorch version of SfmLearner from Tinghui Zhou et al.

    Tagged pytorchPython

    1K stars

  • sniklaus/sepconv-slomo

    an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch

    Tagged pytorchPython

    1K stars

  • microsoft/Tutel

    Tutel MoE: Optimized Mixture-of-Experts Library, Support GptOss/DeepSeek/Kimi-K2/Qwen3 using FP8/NVFP4/MXFP4

    Tagged pytorchC

    1K stars

  • bayesiains/nflows

    Normalizing flows in PyTorch

    Tagged pytorchPython

    1K stars

  • HumanCompatibleAI/overcooked_ai

    A benchmark environment for fully cooperative human-AI performance.

    Tagged pytorchJupyter Notebook

    1K stars

  • WenmuZhou/DBNet.pytorch

    A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization

    Tagged pytorchPython

    1K stars

  • Oldpan/Pytorch-Memory-Utils

    pytorch memory track code

    Tagged pytorchPython

    1K stars

  • wpeebles/gangealing

    Official PyTorch Implementation of "GAN-Supervised Dense Visual Alignment" (CVPR 2022 Oral, Best Paper Finalist)

    Tagged pytorchPython

    1K stars

  • graykode/gpt-2-Pytorch

    Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation

    Tagged pytorchPython

    1K stars

  • allegro/allRank

    allRank is a framework for training learning-to-rank neural models based on PyTorch.

    Tagged pytorchPython

    1K stars

  • xiaoyufenfei/Efficient-Segmentation-Networks

    Lightweight models for real-time semantic segmentationon PyTorch (include SQNet, LinkNet, SegNet, UNet, ENet, ERFNet, EDANet, ESPNet, ESPNetv2, LEDNet, ESNet, FSSNet, CGNet, DABNet, Fast-SCNN, ContextNet, FPENet, etc.)

    Tagged pytorchPython

    1K stars

Packages

“Is” packages are PyTorch itself; ecosystem packages depend on them. The two are counted separately and never added together. Adoption is each registry’s own figure, with its percentile within that registry.

Is 1the technology itself, most-adopted first

  • torch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Listed in the catalogPyPI

    Not published by PyPI

Ecosystem 582packages that depend on it, most-adopted first

  • yolov5

    Packaged version of the Yolov5 object detector

    Depends on torchPyPI

    Not published by PyPI
  • yolov5-face

    Real-time face detection using YOLOv5 - Fork

    Depends on torchPyPI

    Not published by PyPI
  • yolov9py

    YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.

    Depends on torchPyPI

    Not published by PyPI
  • yolox-datamint

    Depends on torchPyPI

    Not published by PyPI
  • yunchang

    a package for long context attention

    Depends on torchPyPI

    Not published by PyPI
  • zuko

    Normalizing flows in PyTorch

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it