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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
- Xilinx/brevitas
Brevitas: neural network quantization in PyTorch
1.6K stars
- D-X-Y/AutoDL-Projects
Automated deep learning algorithms implemented in PyTorch.
1.6K stars
- DiffEqML/torchdyn
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
1.6K stars
- RightNow-AI/autokernel
Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.
1.6K stars
- vturrisi/solo-learn
solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
1.6K stars
- xinntao/EDVR
Winning Solution in NTIRE19 Challenges on Video Restoration and Enhancement (CVPR19 Workshops) - Video Restoration with Enhanced Deformable Convolutional Networks. EDVR has been merged into BasicSR and this repo is a mirror of BasicSR.
1.6K stars
- photosynthesis-team/piq
Measures and metrics for image2image tasks. PyTorch.
1.6K stars
- rwightman/gen-efficientnet-pytorch
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
1.6K stars
- BloodAxe/pytorch-toolbelt
PyTorch extensions for fast R&D prototyping and Kaggle farming
1.6K stars
- kumar-shridhar/PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
1.6K stars
- sniklaus/3d-ken-burns
an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
1.6K stars
- sgrvinod/Deep-Tutorials-for-PyTorch
In-depth tutorials for implementing deep learning models on your own with 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
- custom-colossalai
An integrated large-scale model training system with efficient parallelization techniques
Not published by PyPI - cut-cross-entropy
Code for cut cross entropy, a memory efficient implementation of linear-cross-entropy loss.
Not published by PyPI - d3rlpy
An offline deep reinforcement learning library
Not published by PyPI - dalle2-pytorch
DALL-E 2
Not published by PyPI - dataflex
A data-centric training system for Large Language Models
Not published by PyPI - decider-ai
One-pass typed decisions with calibrated probabilities: decider-2b, decider-35b-a3b and the training recipe
Not published by PyPI - deepctr-torch
Easy-to-use,Modular and Extendible package of deep learning based CTR(Click Through Rate) prediction models with PyTorch
Not published by PyPI - deepdow
Portfolio optimization with deep learning
Not published by PyPI - deepecho
Create sequential synthetic data of mixed types using a GAN.
Not published by PyPI - deeplabcut
Markerless pose-estimation of user-defined features with deep learning
Not published by PyPI - deepparse
A library for parsing multinational street addresses using deep learning.
Not published by PyPI - deeprobust
A PyTorch library for adversarial robustness learning for image and graph data.
Not published by PyPI
Latest news the 3 latest events that mention it
- 33h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026