Technology · Framework
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 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
- VainF/DeepLabV3Plus-Pytorch
Pretrained DeepLabv3 and DeepLabv3+ for Pascal VOC & Cityscapes
2.7K stars
- microsoft/pai
Resource scheduling and cluster management for AI
2.7K stars
- MrGiovanni/UNetPlusPlus
[IEEE TMI Best Paper Award] Official Implementation for UNet++
2.7K stars
- bytedance/InfiniteYou
🔥 [ICCV 2025 Highlight] InfiniteYou: Flexible Photo Recrafting While Preserving Your Identity
2.7K stars
- yxlllc/DDSP-SVC
Real-time end-to-end singing voice conversion system based on DDSP (Differentiable Digital Signal Processing)
2.7K stars
- yerfor/GeneFace
GeneFace: Generalized and High-Fidelity 3D Talking Face Synthesis; ICLR 2023; Official code
2.7K stars
- HypoX64/DeepMosaics
Automatically remove the mosaics in images and videos, or add mosaics to them.
2.7K stars
- swz30/Restormer
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
2.7K stars
- KupynOrest/DeblurGAN
Image Deblurring using Generative Adversarial Networks
2.6K stars
- PeterH0323/Smart_Construction
Base on YOLOv5 Head Person Helmet Detection on Construction Sites，基于目标检测工地安全帽和禁入危险区域识别系统，🚀😆附 YOLOv5 训练自己的数据集超详细教程🚀😆2021.3新增可视化界面❗❗
2.6K stars
- EMI-Group/evox
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
2.6K stars
- znxlwm/pytorch-generative-model-collections
Collection of generative models in Pytorch version.
2.6K 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
- composer
Composer is a PyTorch library that enables you to train neural networks faster, at lower cost, and to higher accuracy.
Not published by PyPI - compressai
A PyTorch library and evaluation platform for end-to-end compression research
Not published by PyPI - compressed-tensors
Library for utilization of compressed safetensors of neural network models
Not published by PyPI - concrete-ml
Concrete ML is an open-source set of tools which aims to simplify the use of fully homomorphic encryption (FHE) for data scientists.
Not published by PyPI - concrete-python
A state-of-the-art homomorphic encryption framework
Not published by PyPI - conformer
The convolutional module from the Conformer paper
Not published by PyPI - contextualized-topic-models
Contextualized Topic Models
Not published by PyPI - controlnet-aux
Auxillary models for controlnet
Not published by PyPI - ctgan
Create tabular synthetic data using a conditional GAN
Not published by PyPI - cuequivariance-ops-torch-cu12
cuequivariance-ops-torch - GPU Accelerated Torch Extensions for Equivariant Primitives
Not published by PyPI - cuequivariance-ops-torch-cu13
cuequivariance-ops-torch - GPU Accelerated Torch Extensions for Equivariant Primitives
Not published by PyPI - curated-transformers
A PyTorch library of transformer models and components
Not published by PyPI
Latest news the 3 latest events that mention it
- 36h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026