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

  • DLR-RM/rl-baselines3-zoo

    A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

    Tagged pytorchPython

    2.9K stars

  • werner-duvaud/muzero-general

    MuZero

    Tagged pytorchPython

    2.9K stars

  • linto-ai/whisper-timestamped

    Multilingual Automatic Speech Recognition with word-level timestamps and confidence

    Tagged pytorchPython

    2.9K stars

  • adapter-hub/adapters

    A Unified Library for Parameter-Efficient and Modular Transfer Learning

    Tagged pytorchPython

    2.8K stars

  • pytorch/xla

    Enabling PyTorch on XLA Devices (e.g. Google TPU)

    Tagged pytorchC++

    2.8K stars

  • autodistill/autodistill

    Images to inference with no labeling (use foundation models to train supervised models).

    Tagged pytorchPython

    2.8K stars

  • mars-project/mars

    Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

    Tagged pytorchPython

    2.7K stars

  • aaron-xichen/pytorch-playground

    Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

    Tagged pytorchPython

    2.7K stars

  • carpedm20/ENAS-pytorch

    PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"

    Tagged pytorchPython

    2.7K stars

  • torch-points3d/torch-points3d

    Pytorch framework for doing deep learning on point clouds.

    Tagged pytorchPython

    2.7K stars

  • zllrunning/video-object-removal

    Just draw a bounding box and you can remove the object you want to remove.

    Tagged pytorchPython

    2.7K stars

  • MLNLP-World/Top-AI-Conferences-Paper-with-Code

    MLNLP:本仓库整理人工智能会议(如 ACL、EMNLP、NAACL、COLING、AAAI、IJCAI、ICLR、NeurIPS、ICML 等)中开源代码的论文。

    Tagged pytorch

    2.7K 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

  • step-audio2

    Step-Audio2: Audio understanding and generation model

    Depends on torchPyPI

    Not published by PyPI
  • stepaudio2-minicpmo

    StepAudio2: Audio tokenizer and TTS model

    Depends on torchPyPI

    Not published by PyPI
  • stylegan2-pytorch

    StyleGan2 in Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • surya-ocr

    OCR, layout, reading order, and table recognition in 90+ languages.

    Depends on torchPyPI

    Not published by PyPI
  • swissarmytransformer

    A transformer-based framework with finetuning as the first class citizen.

    Depends on torchPyPI

    Not published by PyPI
  • synthid-text

    SynthID Text: Identifying AI-generated text content

    Depends on torchPyPI

    Not published by PyPI
  • tab-transformer-pytorch

    Tab Transformer - Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • tabicl

    TabICL: An open tabular foundation model

    Depends on torchPyPI

    Not published by PyPI
  • tabm

    TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling (ICLR 2025).

    Depends on torchPyPI

    Not published by PyPI
  • tabpfn

    TabPFN: Foundation model for tabular data

    Depends on torchPyPI

    Not published by PyPI
  • tabpfn-fork

    TabPFN: Foundation model for tabular data

    Depends on torchPyPI

    Not published by PyPI
  • tensordict

    A dict[str, torch.Tensor] that behaves like one tensor.

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it