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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
- BorealisAI/advertorch
A Toolbox for Adversarial Robustness Research
1.4K stars
- kengz/SLM-Lab
Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
1.4K stars
- huggingface/finetrainers
Scalable and memory-optimized training of diffusion models
1.4K stars
- Replicable-MARL/MARLlib
One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)
1.3K stars
- gempy-project/gempy
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.
1.3K stars
- open-edge-platform/geti
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
1.3K stars
- alibaba/graph-learn
An Industrial Graph Neural Network Framework
1.3K stars
- kuaikuaikim/dface
Deep learning face detection and recognition, implemented by pytorch. (pytorch实现的人脸检测和人脸识别)
1.3K stars
- ikostrikov/pytorch-a3c
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
1.3K stars
- DengBoCong/nlp-paper
自然语言处理领域下的相关论文（附阅读笔记），复现模型以及数据处理等（代码含TensorFlow和PyTorch两版本）
1.3K stars
- Tongjilibo/bert4torch
An elegent pytorch implement of transformers
1.3K stars
- CharlesShang/DCNv2
Deformable Convolutional Networks v2 with Pytorch
1.3K 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
- transformer-smaller-training-vocab
Temporary remove unused tokens during training to save ram and speed.
Not published by PyPI - transparent-background
Make images with transparent background
Not published by PyPI - trellis-3d
TRELLIS is a large 3D asset generation model.
Not published by PyPI - trellis-3d-python
TRELLIS is a large 3D asset generation model.
Not published by PyPI - trl-fpo
Train transformer language models with reinforcement learning.
Not published by PyPI - tts
Deep learning for Text to Speech by Coqui.
Not published by PyPI - tts-webui-chatterbox-tts
Chatterbox: Open Source TTS and Voice Conversion by Resemble AI
Not published by PyPI - tts-webui-index-tts
IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speech
Not published by PyPI - turbodiffusion
TurboDiffusion: video generation acceleration framework that could accelerate end-to-end video generation by 100-205x with negligible video quality loss.
Not published by PyPI - txtai
All-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows
Not published by PyPI - ultralytics
Ultralytics YOLO 🚀 for SOTA object detection, instance segmentation, semantic segmentation, depth estimation, classification, pose estimation, oriented object detection, and multi-object tracking.
Not published by PyPI - ultralytics-thop
Ultralytics THOP package for fast computation of PyTorch model FLOPs and parameters.
Not published by PyPI
Latest news the 3 latest events that mention it
- 24h agoOCT 24, 2026
- 2d agoOCT 22, 2026
- 4mo agoJUL 10, 2026