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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
- kenshohara/3D-ResNets-PyTorch
3D ResNets for Action Recognition (CVPR 2018)
4K stars
- chenyuntc/simple-faster-rcnn-pytorch
A simplified implemention of Faster R-CNN that replicate performance from origin paper
4K stars
- lucidrains/vector-quantize-pytorch
Vector (and Scalar) Quantization, in Pytorch
4K stars
- quark0/darts
Differentiable architecture search for convolutional and recurrent networks
4K stars
- JDAI-CV/fast-reid
SOTA Re-identification Methods and Toolbox
4K stars
- brightmart/albert_zh
A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型
4K stars
- iree-org/iree
A retargetable MLIR-based machine learning compiler and runtime toolkit.
4K stars
- huggingface/huggingface_hub
The official CLI and Python client for the Hugging Face Hub.
4K stars
- neuraloperator/neuraloperator
Learning in infinite dimension with neural operators.
3.9K stars
- Janspiry/Image-Super-Resolution-via-Iterative-Refinement
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
3.9K stars
- cornellius-gp/gpytorch
A highly efficient implementation of Gaussian Processes in PyTorch
3.9K stars
- ikostrikov/pytorch-a2c-ppo-acktr-gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
3.9K 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
- mosaicml-streaming
Streaming lets users create PyTorch compatible datasets that can be streamed from cloud-based object stores
Not published by PyPI - mseep-pyserini
A Python toolkit for reproducible information retrieval research with sparse and dense representations
Not published by PyPI - mseep-txtai
All-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows
Not published by PyPI - msst
Training and inference code for music source separation experiments.
Not published by PyPI - mteb
Massive Text Embedding Benchmark
Not published by PyPI - muscriptor
Music transcription to MIDI and sheet music using a transformer language model
Not published by PyPI - nano-vllm-fork
a lightweight vLLM implementation built from scratch
Not published by PyPI - nebula-ai
AI-Powered Ethical Hacking Assistant
Not published by PyPI - nemo-toolkit
NeMo - a toolkit for Conversational AI
Not published by PyPI - neuralforecast
Time series forecasting suite using deep learning models
Not published by PyPI - neuralprophet
NeuralProphet is an easy to learn framework for interpretable time series forecasting.
Not published by PyPI - neuromancer
Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularization
Not published by PyPI
Latest news the 3 latest events that mention it
- 43h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026