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PyTorch

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Deep learning framework.

Categories
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

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

  • tinyvision/DAMO-YOLO

    DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.

    Tagged pytorchPython

    3.2K

  • megvii-research/NAFNet

    The state-of-the-art image restoration model without nonlinear activation functions.

    Tagged pytorchPython

    3.2K

  • adambielski/siamese-triplet

    Siamese and triplet networks with online pair/triplet mining in PyTorch

    Tagged pytorchPython

    3.2K

  • jettify/pytorch-optimizer

    torch-optimizer -- collection of optimizers for Pytorch

    Tagged pytorchPython

    3.2K

  • cleardusk/3DDFA_V2

    The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.

    Tagged pytorchPython

    3.2K

  • open-mmlab/mmdeploy

    OpenMMLab Model Deployment Framework

    Tagged pytorchPython

    3.1K

  • open-mmlab/mmskeleton

    A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.

    Tagged pytorchPython

    3.1K

  • diegoantognini/pyGAT

    Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

    Tagged pytorchPython

    3.1K

  • dbiir/UER-py

    Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

    Tagged pytorchPython

    3.1K

  • maciejkula/spotlight

    Deep recommender models using PyTorch.

    Tagged pytorchPython

    3K

  • ZQPei/deep_sort_pytorch

    MOT using deepsort and yolov3 with pytorch

    Tagged pytorchPython

    3K

  • osmr/imgclsmob

    Sandbox for training deep learning networks

    Tagged pytorchPython

    3K

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

  • retinaface-py

    RetinaFace: Single-stage Dense Face Localisation in the Wild

    Depends on torchPyPI

    Not published by PyPI
  • rfdetr

    RF-DETR

    Depends on torchPyPI

    Not published by PyPI
  • rl-games

    High-performance Reinforcement Learning framework for games and robotics

    Depends on torchPyPI

    Not published by PyPI
  • rlinf

    Reinforcement Learning Infrastructure for Embodied and Agentic AI

    Depends on torchPyPI

    Not published by PyPI
  • rlinf-openpi

    Physical Intelligence open source repo

    Depends on torchPyPI

    Not published by PyPI
  • roma

    A lightweight library to deal with 3D rotations in PyTorch.

    Depends on torchPyPI

    Not published by PyPI
  • romatch

    Robust Dense Feature Matching

    Depends on torchPyPI

    Not published by PyPI
  • rotary-embedding-torch

    Rotary Embedding - Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • routellm

    A framework for serving and evaluating large language model routers.

    Depends on torchPyPI

    Not published by PyPI
  • rpent-openpi

    Physical Intelligence open source repo

    Depends on torchPyPI

    Not published by PyPI
  • rpent-rlinf

    Reinforcement Learning Infrastructure for Embodied and Agentic AI

    Depends on torchPyPI

    Not published by PyPI
  • rsl-rl-lib

    Fast and simple RL algorithms implemented in PyTorch

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it