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PyTorch

Framework · Meta · Catalog tech@1

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

  • activeloopai/deeplake

    Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

    Tagged pytorchC++

    9.2K

  • NVlabs/Sana

    SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

    Tagged pytorchPython

    9.2K

  • Cadene/pretrained-models.pytorch

    Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

    Tagged pytorchPython

    9.1K

  • pyro-ppl/pyro

    Deep universal probabilistic programming with Python and PyTorch

    Tagged pytorchPython

    9.1K

  • Project-MONAI/MONAI

    AI Toolkit for Healthcare Imaging

    Tagged pytorchPython

    8.7K

  • MVIG-SJTU/AlphaPose

    Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

    Tagged pytorchPython

    8.6K

  • netease-youdao/EmotiVoice

    EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine

    Tagged pytorchPython

    8.5K

  • bitsandbytes-foundation/bitsandbytes

    Accessible large language models via k-bit quantization for PyTorch.

    Tagged pytorchPython

    8.5K

  • aladdinpersson/Machine-Learning-Collection

    A resource for learning about Machine learning & Deep Learning

    Tagged pytorchPython

    8.5K

  • OptimalScale/LMFlow

    An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

    Tagged pytorchPython

    8.5K

  • XPixelGroup/BasicSR

    Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.

    Tagged pytorchPython

    8.4K

  • utkuozbulak/pytorch-cnn-visualizations

    Pytorch implementation of convolutional neural network visualization techniques

    Tagged pytorchPython

    8.2K

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

  • benchpots

    A Python Toolbox for Benchmarking Machine Learning on Partially-Observed Time Series

    Depends on torchPyPI

    Not published by PyPI
  • bert-demo

    Google AI 2018 BERT pytorch implementation

    Depends on torchPyPI

    Not published by PyPI
  • bert-score

    PyTorch implementation of BERT score

    Depends on torchPyPI

    Not published by PyPI
  • bert4torch

    an elegant bert4torch

    Depends on torchPyPI

    Not published by PyPI
  • bertviz

    Attention visualization tool for NLP Transformer models.

    Depends on torchPyPI

    Not published by PyPI
  • bhasa

    Mamba state-space model

    Depends on torchPyPI

    Not published by PyPI
  • bindsnet

    Spiking neural networks for ML in Python

    Depends on torchPyPI

    Not published by PyPI
  • birm-nm-foo

    Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization

    Depends on torchPyPI

    Not published by PyPI
  • bitnet

    bitnet - Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • bitsandbytes

    k-bit optimizers and matrix multiplication routines.

    Depends on torchPyPI

    Not published by PyPI
  • boat-torch

    BOAT: A Compositional Operation Toolbox for Gradient-based Bi-Level Optimization

    Depends on torchPyPI

    Not published by PyPI
  • botorch

    Bayesian Optimization in PyTorch

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it