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

  • raminmh/CfC

    Closed-form Continuous-time Neural Networks

    Tagged pytorchPython

    1.1K stars

  • limbo018/DREAMPlace

    Deep learning toolkit-enabled VLSI placement

    Tagged pytorchC++

    1.1K stars

  • pytorch/benchmark

    TorchBench is a collection of open source benchmarks used to evaluate PyTorch performance.

    Tagged pytorchPython

    1.1K stars

  • 4uiiurz1/pytorch-nested-unet

    PyTorch implementation of UNet++ (Nested U-Net).

    Tagged pytorchPython

    1.1K stars

  • huggingface/optimum-quanto

    A pytorch quantization backend for optimum

    Tagged pytorchPython

    1.1K stars

  • qqlu/Entity

    EntitySeg Toolbox: Towards Open-World and High-Quality Image Segmentation

    Tagged pytorchJupyter Notebook

    1K stars

  • caoscott/SReC

    PyTorch Implementation of "Lossless Image Compression through Super-Resolution"

    Tagged pytorchPython

    1K stars

  • pkhungurn/talking-head-anime-3-demo

    Demo Programs for the "Talking Head(?) Anime from a Single Image 3: Now the Body Too" Project

    Tagged pytorchPython

    1K stars

  • Shawn1993/cnn-text-classification-pytorch

    CNNs for Sentence Classification in PyTorch

    Tagged pytorchPython

    1K stars

  • volcengine/veScale

    Byted PyTorch Distributed for Hyperscale Training of LLMs and RLs

    Tagged pytorchPython

    1K stars

  • descriptinc/melgan-neurips

    GAN-based Mel-Spectrogram Inversion Network for Text-to-Speech Synthesis

    Tagged pytorchPython

    1K stars

  • TorchEnsemble-Community/Ensemble-Pytorch

    A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

    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

  • otxmmaction2

    OpenMMLab Video Understanding Toolbox and Benchmark

    Depends on torchPyPI

    Not published by PyPI
  • oumi

    Oumi - Modeling Platform

    Depends on torchPyPI

    Not published by PyPI
  • outetts

    OuteAI Text-to-Speech (TTS)

    Depends on torchPyPI

    Not published by PyPI
  • peft

    Parameter-Efficient Fine-Tuning (PEFT)

    Depends on torchPyPI

    Not published by PyPI
  • pensiev

    A package for Pensieve (previously known as memos)

    Depends on torchPyPI

    Not published by PyPI
  • petals

    Easy way to efficiently run 100B+ language models without high-end GPUs

    Depends on torchPyPI

    Not published by PyPI
  • physo

    Physical Symbolic Optimization

    Depends on torchPyPI

    Not published by PyPI
  • pi-flash-attn

    Flash Attention: Fast and Memory-Efficient Exact Attention

    Depends on torchPyPI

    Not published by PyPI
  • piml

    A low-code interpretable machine learning toolbox in Python.

    Depends on torchPyPI

    Not published by PyPI
  • pix2tex

    pix2tex: Using a ViT to convert images of equations into LaTeX code.

    Depends on torchPyPI

    Not published by PyPI
  • pixeloe

    Detail-Oriented Pixelization based on Contrast-Aware Outline Expansion.

    Depends on torchPyPI

    Not published by PyPI
  • pnnx

    pnnx is an open standard for PyTorch model interoperability.

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it