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PyTorch
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Deep learning framework.
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- 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 signalsNo 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
103.6K stars
Members 794repositories tagged with one of its aliases, most-starred first
- RUCAIBox/TextBox
TextBox 2.0 is a text generation library with pre-trained language models
1.1K stars
- carpedm20/DiscoGAN-pytorch
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"
1.1K stars
- VITA-Group/EnlightenGAN
[IEEE TIP] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
1.1K stars
- Tencent/TencentPretrain
Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo
1.1K stars
- carefree0910/MachineLearning
Machine learning algorithms implemented by pure numpy
1.1K stars
- agi-brain/xuance
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
1.1K stars
- jla524/fromthetensor
From the Tensor to Stable Diffusion, a rough outline for a 10 week course.
1.1K stars
- guochengqian/PointNeXt
[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
1.1K stars
- rixwew/pytorch-fm
Factorization Machine models in PyTorch
1.1K stars
- Stonesjtu/pytorch_memlab
Profiling and inspecting memory in pytorch
1.1K stars
- mert-kurttutan/torchview
torchview: visualize pytorch models
1.1K stars
- orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
1.1K 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
Not published by PyPI
Ecosystem 582packages that depend on it, most-adopted first
- lerobot
🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch
Not published by PyPI - lerobot-robodriver
🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch
Not published by PyPI - lhotse
Data preparation for speech processing models training.
Not published by PyPI - liger-kernel
Efficient Triton kernels for LLM Training
Not published by PyPI - liger-kernel-nightly
Efficient Triton kernels for LLM Training
Not published by PyPI - lightautoml
Fast and customizable framework for automatic ML model creation (AutoML)
Not published by PyPI - lighteval
A lightweight and configurable evaluation package
Not published by PyPI - lightly
A deep learning package for self-supervised learning
Not published by PyPI - lightning
The Deep Learning framework to train, deploy, and ship AI products Lightning fast.
Not published by PyPI - lightning-thunder
Lightning Thunder is a source-to-source compiler for PyTorch, enabling PyTorch programs to run on different hardware accelerators and graph compilers.
Not published by PyPI - lightweight-gan
Lightweight GAN
Not published by PyPI - linear-operator
A linear operator implementation, primarily designed for finite-dimensional positive definite operators (i.e. kernel matrices).
Not published by PyPI
Latest news the 3 latest events that mention it
- 26h agoOCT 24, 2026
- 2d agoOCT 22, 2026
- 4mo agoJUL 10, 2026