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

  • GOATmessi8/RFBNet

    Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018

    Tagged pytorchPython

    1.4K stars

  • jrzaurin/pytorch-widedeep

    A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch

    Tagged pytorchPython

    1.4K stars

  • bermanmaxim/LovaszSoftmax

    Code for the Lovász-Softmax loss (CVPR 2018)

    Tagged pytorchJupyter Notebook

    1.4K stars

  • explosion/spacy-transformers

    🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

    Tagged pytorchPython

    1.4K stars

  • MedMNIST/MedMNIST

    [pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification

    Tagged pytorchPython

    1.4K stars

  • RahulSChand/gpu_poor

    Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization

    Tagged pytorchJavaScript

    1.4K stars

  • swz30/MPRNet

    [CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.

    Tagged pytorchPython

    1.4K stars

  • xl0/lovely-tensors

    Tensors, for human consumption

    Tagged pytorchJupyter Notebook

    1.4K stars

  • Denys88/rl_games

    RL implementations

    Tagged pytorchJupyter Notebook

    1.4K stars

  • GradientHQ/parallax

    Parallax is a distributed model serving framework that lets you build your own AI cluster anywhere

    Tagged pytorchPython

    1.4K stars

  • L1aoXingyu/Deep-Learning-Project-Template

    A best practice for deep learning project template architecture.

    Tagged pytorchPython

    1.4K stars

  • yinboc/liif

    Learning Continuous Image Representation with Local Implicit Image Function, in CVPR 2021 (Oral)

    Tagged pytorchPython

    1.4K 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

  • wicky-vllm

    a lightweight vLLM implementation built from scratch

    Depends on torchPyPI

    Not published by PyPI
  • wisup-e2m

    Everything to Markdown.

    Depends on torchPyPI

    Not published by PyPI
  • worker-automate-hub

    Worker Automate HUB é uma aplicação para automatizar rotinas de RPA nos ambientes Argenta.

    Depends on torchPyPI

    Not published by PyPI
  • x-transformers

    X-Transformers

    Depends on torchPyPI

    Not published by PyPI
  • xformers

    XFormers: A collection of composable Transformer building blocks.

    Depends on torchPyPI

    Not published by PyPI
  • xgrammar

    Efficient, Flexible and Portable Structured Generation

    Depends on torchPyPI

    Not published by PyPI
  • xh-pdf-parser

    A practical tool for converting PDF to Markdown

    Depends on torchPyPI

    Not published by PyPI
  • xinference

    Model Serving Made Easy

    Depends on torchPyPI

    Not published by PyPI
  • xlstm

    A novel LSTM variant with promising performance compared to Transformers or State Space Models.

    Depends on torchPyPI

    Not published by PyPI
  • xtest-bert-score

    PyTorch implementation of BERT score for xtest

    Depends on torchPyPI

    Not published by PyPI
  • xtuner

    An efficient, flexible and full-featured toolkit for fine-tuning large models

    Depends on torchPyPI

    Not published by PyPI
  • xuance

    XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library.

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it