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
- kubeflow/kubeflow
The Cloud Native AI Platform
15.9K stars
- microsoft/Bringing-Old-Photos-Back-to-Life
Bringing Old Photo Back to Life (CVPR 2020 oral)
15.7K stars
- GeeeekExplorer/nano-vllm
Nano vLLM
15.7K stars
- kyegomez/OpenMythos
A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.
14.9K stars
- NVIDIA/DeepLearningExamples
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
14.9K stars
- NVIDIA/TensorRT-LLM
TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.
14.8K stars
- BlinkDL/RWKV-LM
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
14.7K stars
- flairNLP/flair
A very simple framework for state-of-the-art Natural Language Processing (NLP)
14.4K stars
- mlfoundations/open_clip
An open source implementation of CLIP.
14.2K stars
- WongKinYiu/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
14.2K stars
- isl-org/Open3D
Open3D: A Modern Library for 3D Data Processing
14K stars
- DLR-RM/stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
13.9K 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
- torchscale
Transformers at any scale
Not published by PyPI - torchscale-gml
Transformers at any scale
Not published by PyPI - torchsde
SDE solvers and stochastic adjoint sensitivity analysis in PyTorch.
Not published by PyPI - torchsr
Super Resolution Networks for pytorch
Not published by PyPI - torchtext
Text utilities, models, transforms, and datasets for PyTorch.
Not published by PyPI - torchtnt
A lightweight library for PyTorch training tools and utilities
Not published by PyPI - torchtyping
Runtime type annotations for the shape, dtype etc. of PyTorch Tensors.
Not published by PyPI - torchvision
image and video datasets and models for torch deep learning
Not published by PyPI - torchviz
A small package to create visualizations of PyTorch execution graphs
Not published by PyPI - torchxrayvision
TorchXRayVision: A library of chest X-ray datasets and models
Not published by PyPI - totalsegmentator
Robust segmentation of 117 classes in CT images.
Not published by PyPI - transformer-engine-torch
Transformer acceleration library - Torch Lib
Not published by PyPI
Latest news the 3 latest events that mention it
- 14h agoOCT 24, 2026
- 2d agoOCT 22, 2026
- 4mo agoJUL 10, 2026