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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
- deepspeedai/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
43.2K stars
- 2noise/ChatTTS
A generative speech model for daily dialogue.
39.9K stars
- OpenBMB/VoxCPM
VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning
38.3K stars
- TencentARC/GFPGAN
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
37.7K stars
- huggingface/pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
37.2K stars
- xinntao/Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
37K stars
- babysor/MockingBird
🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time
36.9K stars
- huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
34.6K stars
- lutzroeder/netron
Visualizer for neural network, deep learning and machine learning models
33.5K stars
- open-mmlab/mmdetection
OpenMMLab Detection Toolbox and Benchmark
33K stars
- Lightning-AI/pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
31.4K stars
- NandhaKishorM/laya
Non-autoregressive System 1 decision engine. Typed choice, score and yes/no decisions over any text in a single forward pass, in 100+ languages, with a router that picks the right checkpoint per request.
30.1K 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
- torchdyn
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods.
Not published by PyPI - torchensemble
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model
Not published by PyPI - torchfcpe
The official Pytorch implementation of Fast Context-based Pitch Estimation (FCPE)
Not published by PyPI - Not published by PyPI
- torchgeo
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Not published by PyPI - torchio
Tools for medical image processing with PyTorch
Not published by PyPI - torchmetrics
PyTorch native Metrics
Not published by PyPI - torchprofile
Count the MACs / FLOPs of PyTorch models
Not published by PyPI - torchquantum
Quantum Computing in PyTorch
Not published by PyPI - torchrl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning
Not published by PyPI - torchrl-nightly
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning
Not published by PyPI - torchrunx
Automatically initialize distributed PyTorch environments
Not published by PyPI
Latest news the 3 latest events that mention it
- 13h agoOCT 24, 2026
- 48h agoOCT 22, 2026
- 4mo agoJUL 10, 2026