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PyTorch
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Deep learning framework.
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- 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
- THUDM/SwissArmyTransformer
SwissArmyTransformer is a flexible and powerful library to develop your own Transformer variants.
1.1K stars
- datadreamer-dev/DataDreamer
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models. 🤖💤
1.1K stars
- microsoft/Windows-Machine-Learning
Samples and Tools for Windows ML.
1.1K stars
- AdaptiveMotorControlLab/CEBRA
Learnable latent embeddings for joint behavioral and neural analysis - Official implementation of CEBRA
1.1K stars
- bearpaw/pytorch-pose
A PyTorch toolkit for 2D Human Pose Estimation.
1.1K stars
- ndif-team/nnsight
The nnsight package enables interpreting and manipulating the internals of deep learned models.
1.1K stars
- ryfeus/lambda-packs
Precompiled packages for AWS Lambda
1.1K stars
- vietnh1009/Super-mario-bros-A3C-pytorch
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
1.1K stars
- gordicaleksa/pytorch-original-transformer
My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.
1.1K stars
- snap-research/EfficientFormer
EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
1.1K stars
- Res2Net/Res2Net-PretrainedModels
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
1.1K stars
- mit-han-lab/gan-compression
[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs
1.1K 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
- tensordict-nightly
A dict[str, torch.Tensor] that behaves like one tensor.
Not published by PyPI - tensorizer
A tool for fast PyTorch module, model, and tensor serialization + deserialization.
Not published by PyPI - 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.
Not published by PyPI - textattack
A library for generating text adversarial examples
Not published by PyPI - thop
A tool to count the FLOPs of PyTorch model.
Not published by PyPI - tianshou
A Library for Deep Reinforcement Learning
Not published by PyPI - tile-kernels
Tilelang-based kernels.
Not published by PyPI - tilelang
A tile level programming language to generate high performance code.
Not published by PyPI - tilert
TileRT: Tile-Based Runtime for Ultra-Low-Latency LLM Inference.
Not published by PyPI - timecopilot-chronos-forecasting
Chronos: Pretrained models for time series forecasting
Not published by PyPI - timecopilot-timesfm
Open weights time-series foundation model from Google Research.
Not published by PyPI - timm
PyTorch Image Models
Not published by PyPI
Latest news the 3 latest events that mention it
- 21h agoOCT 24, 2026
- 2d agoOCT 22, 2026
- 4mo agoJUL 10, 2026