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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

  • CLUEbenchmark/CLUE

    中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

    Tagged pytorchPython

    4.3K

  • richzhang/PerceptualSimilarity

    LPIPS metric. pip install lpips

    Tagged pytorchPython

    4.3K

  • Nixtla/neuralforecast

    Scalable and user friendly neural :brain: forecasting algorithms.

    Tagged pytorchPython

    4.3K

  • SwanHubX/SwanLab

    ⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports Cloud / Self-hosted use. Integrated with PyTorch / Transformers / verl / LLaMA Factory / ms-swift / Ultralytics / MMEngine / Keras etc.

    Tagged pytorchPython

    4.2K

  • apachecn/pytorch-doc-zh

    Pytorch 中文文档

    Tagged pytorchShell

    4.2K

  • metavoiceio/metavoice-src

    Foundational model for human-like, expressive TTS

    Tagged pytorchPython

    4.2K

  • torchgeo/torchgeo

    TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

    Tagged pytorchPython

    4.2K

  • pqpo/SmartCropper

    🔥 A library for cropping image in a smart way that can identify the border and correct the cropped image. 智能图片裁剪框架。自动识别边框，手动调节选区，使用透视变换裁剪并矫正选区；适用于身份证，名片，文档等照片的裁剪。

    Tagged pytorchJava

    4.1K

  • IDEA-CCNL/Fengshenbang-LM

    Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。

    Tagged pytorchPython

    4.1K

  • mlfoundations/open_flamingo

    An open-source framework for training large multimodal models.

    Tagged pytorchPython

    4.1K

  • deepchecks/deepchecks

    Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

    Tagged pytorchPython

    4.1K

  • sksq96/pytorch-summary

    Model summary in PyTorch similar to `model.summary()` in Keras

    Tagged pytorchPython

    4.1K

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

  • retinaface-py

    RetinaFace: Single-stage Dense Face Localisation in the Wild

    Depends on torchPyPI

    Not published by PyPI
  • rfdetr

    RF-DETR

    Depends on torchPyPI

    Not published by PyPI
  • rl-games

    High-performance Reinforcement Learning framework for games and robotics

    Depends on torchPyPI

    Not published by PyPI
  • rlinf

    Reinforcement Learning Infrastructure for Embodied and Agentic AI

    Depends on torchPyPI

    Not published by PyPI
  • rlinf-openpi

    Physical Intelligence open source repo

    Depends on torchPyPI

    Not published by PyPI
  • roma

    A lightweight library to deal with 3D rotations in PyTorch.

    Depends on torchPyPI

    Not published by PyPI
  • romatch

    Robust Dense Feature Matching

    Depends on torchPyPI

    Not published by PyPI
  • rotary-embedding-torch

    Rotary Embedding - Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • routellm

    A framework for serving and evaluating large language model routers.

    Depends on torchPyPI

    Not published by PyPI
  • rpent-openpi

    Physical Intelligence open source repo

    Depends on torchPyPI

    Not published by PyPI
  • rpent-rlinf

    Reinforcement Learning Infrastructure for Embodied and Agentic AI

    Depends on torchPyPI

    Not published by PyPI
  • rsl-rl-lib

    Fast and simple RL algorithms implemented in PyTorch

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it