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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
- milesial/Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
11.7K stars
- kornia/kornia
🐍 Geometric Computer Vision Library for Spatial AI
11.4K stars
- wandb/wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
11.3K stars
- QuentinFuxa/WhisperLiveKit
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
11.1K stars
- thu-ml/tianshou
An elegant PyTorch deep reinforcement learning library.
11K stars
- autogluon/autogluon
Fast and Accurate ML in 3 Lines of Code
10.8K stars
- Megvii-BaseDetection/YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
10.6K stars
- ultralytics/yolov3
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
10.6K stars
- bigscience-workshop/petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
10.6K stars
- vwxyzjn/cleanrl
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
10.5K stars
- snakers4/silero-vad
Silero VAD: pre-trained enterprise-grade Voice Activity Detector
10.3K stars
- satellite-image-deep-learning/techniques
Techniques for deep learning with satellite & aerial imagery
10.3K 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
- accelerate
Accelerate
Not published by PyPI - acvl-utils
Super cool utilities that we just love to use
Not published by PyPI - adam-atan2-pytorch
Adam-atan2 for Pytorch
Not published by PyPI - adaptive-classifier
A flexible, adaptive classification system for dynamic text classification
Not published by PyPI - ai-agents
An Open-source Framework for Autonomous Language Agents
Not published by PyPI - ai-dynamo-vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - ai-gradio
A Python package for creating Gradio applications with AI models
Not published by PyPI - ai2-olmo-core
Core training module for the Open Language Model (OLMo)
Not published by PyPI - aiconfig-extension-hugging-face
An extension for using Hugging Face tasks to parse models for AIConfig.
Not published by PyPI - aiconfig-extension-llama-guard
An extension for using LLama Guard with aiconfig
Not published by PyPI - aideml
Autonomous AI for Data Science and Machine Learning
Not published by PyPI - airllm
AirLLM runs 70B large language models on a single 4GB GPU without quantization, distillation or pruning. Kimi K3 2.8T on under 4GB, Qwen3.8-Flash-Next 125B on 6GB, DeepSeek-V3 671B on ~12GB. Train Qwen3.8-Flash-Next under 6GB.
Not published by PyPI
Latest news the 3 latest events that mention it
- 12h agoOCT 24, 2026
- 47h agoOCT 22, 2026
- 4mo agoJUL 10, 2026