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PyTorch
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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
- ai-forever/ru-dalle
Generate images from texts. In Russian
1.6K stars
- CoinCheung/BiSeNet
Add bisenetv2. My implementation of BiSeNet
1.6K stars
- yoshitomo-matsubara/torchdistill
A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods presented at TPAMI, CVPR, ICLR, ECCV, NeurIPS, ICCV, AAAI, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
1.6K stars
- jeffffffli/HybrIK
Official code of "HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation", CVPR 2021
1.6K stars
- pypose/pypose
A library for differentiable robotics on manifolds.
1.6K stars
- ialhashim/DenseDepth
High Quality Monocular Depth Estimation via Transfer Learning
1.6K stars
- kakaobrain/fast-autoaugment
Official Implementation of 'Fast AutoAugment' in PyTorch.
1.6K stars
- kotaro-kinoshita/yomitoku
YomiTokuはAIを活用した日本語文書解析エンジンを提供するPythonパッケージです。 Yomitoku is an AI-powered document image analysis package designed specifically for the Japanese language.
1.6K stars
- ai-forever/ghost
A new one shot face swap approach for image and video domains
1.6K stars
- DeepGraphLearning/torchdrug
A powerful and flexible machine learning platform for drug discovery
1.6K stars
- microsoft/Semi-supervised-learning
A Unified Semi-Supervised Learning Codebase (NeurIPS'22)
1.6K stars
- lufficc/SSD
High quality, fast, modular reference implementation of SSD in PyTorch
1.6K 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
- topai-faster-whisper
Faster Whisper transcription with CTranslate2
Not published by PyPI - torch-audiomentations
A Pytorch library for audio data augmentation. Inspired by audiomentations. Useful for deep learning.
Not published by PyPI - torch-c-dlpack-ext
torch c dlpack ext
Not published by PyPI - torch-directml
A DirectML backend for hardware acceleration in PyTorch.
Not published by PyPI - torch-einops-utils
Personal utility functions
Not published by PyPI - torch-ema
PyTorch library for computing moving averages of model parameters.
Not published by PyPI - torch-fidelity
High-fidelity performance metrics for generative models in PyTorch
Not published by PyPI - torch-geometric-temporal
A Temporal Extension Library for PyTorch Geometric.
Not published by PyPI - torch-lr-finder
Pytorch implementation of the learning rate range test
Not published by PyPI - torch-npu
NPU bridge for PyTorch
Not published by PyPI - torch-optimizer
pytorch-optimizer
Not published by PyPI - 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