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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
- Rikorose/DeepFilterNet
Noise supression using deep filtering
4.8K stars
- CarperAI/trlx
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
4.8K stars
- open-mmlab/mmocr
OpenMMLab Text Detection, Recognition and Understanding Toolbox
4.8K stars
- hyunwoongko/transformer
Transformer: PyTorch Implementation of "Attention Is All You Need"
4.7K stars
- Tencent/TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
4.7K stars
- WhisperSpeech/WhisperSpeech
An Open Source text-to-speech system built by inverting Whisper.
4.7K stars
- sweetice/Deep-reinforcement-learning-with-pytorch
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
4.7K stars
- PINTO0309/PINTO_model_zoo
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.
4.6K stars
- RUCAIBox/RecBole
A unified, comprehensive and efficient recommendation library
4.6K stars
- NVlabs/tiny-cuda-nn
Lightning fast C++/CUDA neural network framework
4.5K stars
- modelscope/ClearerVoice-Studio
An AI-Powered Speech Processing Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Enhancement, Separation, and Target Speaker Extraction, etc.
4.5K stars
- OAID/Tengine
Tengine is a lite, high performance, modular inference engine for embedded device
4.5K 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
- chatterbox-tts
Chatterbox: Open Source TTS and Voice Conversion by Resemble AI
Not published by PyPI - chattts
A generative speech model for daily dialogue
Not published by PyPI - checkpoint-engine
checkpoint-engine is a lightweight, decoupling and efficient weight update middleware
Not published by PyPI - chemprop
Molecular Property Prediction with Message Passing Neural Networks
Not published by PyPI - chronos-forecasting
Chronos: Pretrained models for time series forecasting
Not published by PyPI - clean-fid
FID calculation in PyTorch with proper image resizing and quantization steps
Not published by PyPI - clearvoice
A unified inference platform for speech processing tasks
Not published by PyPI - clip-interrogator
Generate a prompt from an image
Not published by PyPI - cmq-test
vLLM Ascend backend plugin
Not published by PyPI - coca-pytorch
CoCa, Contrastive Captioners are Image-Text Foundation Models - Pytorch
Not published by PyPI - colpali-engine
The code used to train and run inference with the ColPali architecture.
Not published by PyPI - compel
A prompting enhancement library for transformers-type text embedding systems.
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