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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
- AshwinRJ/Federated-Learning-PyTorch
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
1.4K stars
- voice-cloning-app/Voice-Cloning-App
A Python/Pytorch app for easily synthesising human voices
1.4K stars
- ymcui/Chinese-ELECTRA
Pre-trained Chinese ELECTRA（中文ELECTRA预训练模型）
1.4K stars
- KaiyangZhou/Dassl.pytorch
A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.
1.4K stars
- nianticlabs/simplerecon
[ECCV 2022] SimpleRecon: 3D Reconstruction Without 3D Convolutions
1.4K stars
- qfgaohao/pytorch-ssd
MobileNetV1, MobileNetV2, VGG based SSD/SSD-lite implementation in Pytorch 1.0 / Pytorch 0.4. Out-of-box support for retraining on Open Images dataset. ONNX and Caffe2 support. Experiment Ideas like CoordConv.
1.4K stars
- wenet-e2e/wespeaker
Research and Production Oriented Speaker Verification, Recognition and Diarization Toolkit
1.4K stars
- kitops-ml/kitops
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.
1.4K stars
- Tencent-Hunyuan/AuK
AuK: An Open-Source Foundational Model for Speech Generation and Editing
1.4K stars
- apple-aiml-research/ml-aim
This repository provides the code and model checkpoints for AIMv1 and AIMv2 research projects.
1.4K stars
- torchgan/torchgan
Research Framework for easy and efficient training of GANs based on Pytorch
1.4K stars
- SKTBrain/KoBERT
Korean BERT pre-trained cased (KoBERT)
1.4K 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
- new-gfpgan
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration
Not published by PyPI - nextai-vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - nixl-cu12
NIXL Python API
Not published by PyPI - nixl-cu13
NIXL Python API
Not published by PyPI - nnaudio
A fast GPU audio processing toolbox with 1D convolutional neural network
Not published by PyPI - nnsight
Interpreting and manipulating the internals of neural networks.
Not published by PyPI - nnunetv2
nnU-Net is a framework for out-of-the box image segmentation.
Not published by PyPI - nnunetv2-neuropoly
NeuroPoly fork of nnU-Net
Not published by PyPI - nnunetv2ml
nnU-Net is a framework for out-of-the box image segmentation.
Not published by PyPI - nvdlfw-inspect
Facilitates debugging convergence issues and testing new algorithms/recipes for training LLMs using Nvidia libraries.
Not published by PyPI - nvidia-modelopt
Nvidia Model Optimizer: A unified library of SOTA model optimization techniques like quantization, pruning, Neural Architecture Search (NAS), distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Not published by PyPI - nvidia-physicsnemo
A deep learning framework for AI-driven multi-physics systems
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