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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
- svip-lab/impersonator
PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
1.7K stars
- airaria/TextBrewer
A PyTorch-based knowledge distillation toolkit for natural language processing
1.7K stars
- EnzymeAD/Enzyme
High-performance automatic differentiation of LLVM and MLIR.
1.7K stars
- kubeflow/katib
Automated Machine Learning on Kubernetes
1.7K stars
- BindsNET/bindsnet
Simulation of spiking neural networks (SNNs) using PyTorch.
1.7K stars
- VITA-Group/TransGAN
[NeurIPS‘2021] "TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up", Yifan Jiang, Shiyu Chang, Zhangyang Wang
1.7K stars
- tensorly/tensorly
TensorLy: Tensor Learning in Python.
1.7K stars
- lightly-ai/lightly-train
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
1.7K stars
- LoSealL/VideoSuperResolution
A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.
1.7K stars
- graph4ai/graph4nlp
Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!
1.7K stars
- microsoft/EdgeML
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
1.7K stars
- pytorch-tabular/pytorch_tabular
A unified framework for Deep Learning Models on tabular data
1.7K 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
- diffq-fixed
Differentiable quantization framework for PyTorch -- fixed for compatibility with Python 3.11+
Not published by PyPI - dlr-moge
MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
Not published by PyPI - docling-ibm-models
This package contains the AI models used by the Docling PDF conversion package
Not published by PyPI - docta-ai
Docta.ai
Not published by PyPI - dora-search
Easy grid searches for ML.
Not published by PyPI - Not published by PyPI
- e3nn
Equivariant convolutional neural networks for the group E(3) of 3 dimensional rotations, translations, and mirrors.
Not published by PyPI - eagle-llm
Accelerating LLMs by 3x with No Quality Loss
Not published by PyPI - early-stopping-pytorch
A PyTorch utility package for Early Stopping
Not published by PyPI - earth2studio
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
Not published by PyPI - easyocr
End-to-End Multi-Lingual Optical Character Recognition (OCR) Solution
Not published by PyPI - effdet
EfficientDet for PyTorch
Not published by PyPI
Latest news the 3 latest events that mention it
- 38h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026