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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
- tinyvision/DAMO-YOLO
DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.
3.2K stars
- megvii-research/NAFNet
The state-of-the-art image restoration model without nonlinear activation functions.
3.2K stars
- adambielski/siamese-triplet
Siamese and triplet networks with online pair/triplet mining in PyTorch
3.2K stars
- jettify/pytorch-optimizer
torch-optimizer -- collection of optimizers for Pytorch
3.2K stars
- cleardusk/3DDFA_V2
The official PyTorch implementation of Towards Fast, Accurate and Stable 3D Dense Face Alignment, ECCV 2020.
3.2K stars
- open-mmlab/mmdeploy
OpenMMLab Model Deployment Framework
3.1K stars
- open-mmlab/mmskeleton
A OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
3.1K stars
- diegoantognini/pyGAT
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
3.1K stars
- dbiir/UER-py
Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo
3.1K stars
- maciejkula/spotlight
Deep recommender models using PyTorch.
3K stars
- ZQPei/deep_sort_pytorch
MOT using deepsort and yolov3 with pytorch
3K stars
- osmr/imgclsmob
Sandbox for training deep learning networks
3K 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
- lion-pytorch
Lion Optimizer - Pytorch
Not published by PyPI - litdata
The Deep Learning framework to train, deploy, and ship AI products Lightning fast.
Not published by PyPI - litert-torch
Support PyTorch model conversion with LiteRT.
Not published by PyPI - litgpt
Hackable implementation of state-of-the-art open-source LLMs
Not published by PyPI - llada
Large Language Diffusion Models
Not published by PyPI - llamafirewall
LlamaFirewall is a framework designed to detect and mitigate AI centric security risks, supporting multiple layers of inputs and outputs, such as typical LLM chat and more advanced multi-step agentic operations. It consists of a set of scanners for different security risks.
Not published by PyPI - llava-torch
Towards GPT-4 like large language and visual assistant.
Not published by PyPI - llm-foundry
LLM Foundry
Not published by PyPI - llm-guard
LLM-Guard is a comprehensive tool designed to fortify the security of Large Language Models (LLMs). By offering sanitization, detection of harmful language, prevention of data leakage, and resistance against prompt injection attacks, LLM-Guard ensures that your interactions with LLMs remain safe and secure.
Not published by PyPI - llmcompressor
A library for compressing large language models utilizing the latest techniques and research in the field for both training aware and post training techniques. The library is designed to be flexible and easy to use on top of PyTorch and HuggingFace Transformers, allowing for quick experimentation.
Not published by PyPI - lmcache
A LLM serving engine extension to reduce TTFT and increase throughput, especially under long-context scenarios.
Not published by PyPI - lmeval-trunk
A framework for evaluating language models
Not published by PyPI
Latest news the 3 latest events that mention it
- 44h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026