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

  • iver56/torch-audiomentations

    Fast audio data augmentation in PyTorch. Inspired by audiomentations. Useful for deep learning.

    Tagged pytorchPython

    1.2K stars

  • GaParmar/clean-fid

    PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]

    Tagged pytorchPython

    1.2K stars

  • cure-lab/MagicDrive

    [ICLR24] Official implementation of the paper “MagicDrive: Street View Generation with Diverse 3D Geometry Control”

    Tagged pytorchPython

    1.2K stars

  • yandex-research/rtdl

    Research on Tabular Deep Learning: Papers & Packages

    Tagged pytorchPython

    1.2K stars

  • alexandre01/deepsvg

    [NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.

    Tagged pytorchJupyter Notebook

    1.2K stars

  • oneapi-src/oneAPI-samples

    Samples for Intel® oneAPI Toolkits

    Tagged pytorchC++

    1.2K stars

  • sirius-ai/LPRNet_Pytorch

    Pytorch Implementation For LPRNet, A High Performance And Lightweight License Plate Recognition Framework.

    Tagged pytorchPython

    1.2K stars

  • PKU-Alignment/omnisafe

    JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.

    Tagged pytorchPython

    1.2K stars

  • chengtan9907/OpenSTL

    OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

    Tagged pytorchPython

    1.2K stars

  • lhotse-speech/lhotse

    Tools for handling multimodal data in machine learning projects.

    Tagged pytorchPython

    1.2K stars

  • pkhungurn/talking-head-anime-2-demo

    Demo programs for the Talking Head Anime from a Single Image 2: More Expressive project.

    Tagged pytorchPython

    1.2K stars

  • Sharpiless/Yolov5-Deepsort

    最新版本yolov5+deepsort目标检测和追踪,能够显示目标类别,支持5.0版本可训练自己数据集

    Tagged pytorchPython

    1.2K 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

  • torch-pruning

    Towards Any Structural Pruning

    Depends on torchPyPI

    Not published by PyPI
  • torch-rechub

    A lightweight, efficient, and easy-to-use PyTorch recommendation system framework.

    Depends on torchPyPI

    Not published by PyPI
  • torch-stoi

    Computes Short Term Objective Intelligibility in PyTorch

    Depends on torchPyPI

    Not published by PyPI
  • torch-tensorrt

    Torch-TensorRT is a package which allows users to automatically compile PyTorch and TorchScript modules to TensorRT while remaining in PyTorch

    Depends on torchPyPI

    Not published by PyPI
  • torch-tensorrt-rtx

    Torch-TensorRT is a package which allows users to automatically compile PyTorch and TorchScript modules to TensorRT while remaining in PyTorch

    Depends on torchPyPI

    Not published by PyPI
  • torchcam

    Class activation maps (Grad-CAM, Score-CAM, LeGrad and more) for PyTorch CNNs and Vision Transformers

    Depends on torchPyPI

    Not published by PyPI
  • torchcde

    Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.

    Depends on torchPyPI

    Not published by PyPI
  • torchcfm

    Conditional Flow Matching for Fast Continuous Normalizing Flow Training.

    Depends on torchPyPI

    Not published by PyPI
  • torchcrepe

    Pytorch implementation of CREPE pitch tracker

    Depends on torchPyPI

    Not published by PyPI
  • torchdata

    Composable data loading modules for PyTorch

    Depends on torchPyPI

    Not published by PyPI
  • torchdiffeq

    ODE solvers and adjoint sensitivity analysis in PyTorch.

    Depends on torchPyPI

    Not published by PyPI
  • torchdistill

    A Modular, Configuration-Driven Framework for Knowledge Distillation. Trained models, training logs and configurations are available for ensuring the reproducibility.

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it