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
- ayooshkathuria/pytorch-yolo-v3
A PyTorch implementation of the YOLO v3 object detection algorithm
3.3K stars
- NVIDIA/physicsnemo
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
3.3K stars
- open-mmlab/mmselfsup
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
3.3K stars
- deepdoctection/deepdoctection
A Repo For Document AI
3.3K stars
- zhanghang1989/ResNeSt
ResNeSt: Split-Attention Networks
3.3K stars
- lakesoul-io/LakeSoul
LakeSoul is an end-to-end, realtime cloud-native Lakehouse framework for fast data ingestion, concurrent updates, incremental analytics, multimodal data processing and vector search — powering next-generation BI and AI workloads.
3.3K stars
- Pointcept/Pointcept
Pointcept: Perceive the world with sparse points, a codebase for point cloud perception research. Latest works: Utonia (ICML'26), Concerto (NeurIPS'25), Sonata (CVPR'25 Highlight), PTv3 (CVPR'24 Oral)
3.2K stars
- determined-ai/determined
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
3.2K stars
- seungeunrho/minimalRL
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
3.2K stars
- mkocabas/VIBE
Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
3.2K stars
- webdataset/webdataset
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
3.2K stars
- Djdefrag/QualityScaler
QualityScaler - image/video AI upscaler app
3.2K 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
- fedml
A research and production integrated edge-cloud library for federated/distributed machine learning at anywhere at any scale.
Not published by PyPI - flagembedding
FlagEmbedding
Not published by PyPI - flair
A very simple framework for state-of-the-art NLP
Not published by PyPI - flair-pos
A very simple framework for state-of-the-art NLP
Not published by PyPI - flash-attn
Flash Attention: Fast and Memory-Efficient Exact Attention
Not published by PyPI - flash-attn-4
Flash Attention CUTE (CUDA Template Engine) implementation
Not published by PyPI - flashinfer-python
FlashInfer: Kernel Library for LLM Serving
Not published by PyPI - flashrag-dev
A library for efficient Retrieval-Augmented Generation research
Not published by PyPI - flow-matching
Flow Matching for Generative Modeling
Not published by PyPI - freetoken
Local MoE-offload LLM inference runtime with OpenAI- and Anthropic-compatible APIs
Not published by PyPI - galore-torch
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Not published by PyPI - gandlf
PyTorch-based framework that handles segmentation/regression/classification using various DL architectures for medical imaging.
Not published by PyPI
Latest news the 3 latest events that mention it
- 37h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026