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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
- microsoft/onnxruntime
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
22K stars
- huggingface/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
21.7K stars
- onnx/onnx
Open standard for machine learning interoperability
21.6K stars
- AI4Finance-Foundation/FinGPT
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
21.3K stars
- modelscope/FunASR
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
20.6K stars
- stas00/ml-engineering
Machine Learning Engineering Open Book
19.1K stars
- arc53/DocsGPT
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
18.3K stars
- sczhou/CodeFormer
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
18.2K stars
- cvat-ai/cvat
Computer Vision Annotation Tool (CVAT) is a leading platform for building high-quality visual datasets for vision AI. It offers open-source, cloud, and enterprise products, as well as labeling services, for image, video, and 3D annotation with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
16.8K stars
- lukas-blecher/LaTeX-OCR
pix2tex: Using a ViT to convert images of equations into LaTeX code.
16.6K stars
- tracel-ai/burn
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
16K stars
- camenduru/stable-diffusion-webui-colab
stable diffusion webui colab
15.9K 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
- 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
- 13h agoOCT 24, 2026
- 47h agoOCT 22, 2026
- 4mo agoJUL 10, 2026