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PyTorch

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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 signals

No 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

    Official repositoryPython

    103.6K

Members 794repositories tagged with one of its aliases, most-starred first

  • ZhaoJ9014/face.evoLVe

    🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

    Tagged pytorchPython

    3.6K

  • pytorch/rl

    A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

    Tagged pytorchPython

    3.6K

  • zhaoyingjun/chatbot

    Chatbot继续沿着LLM前进，近期更新小参数量SLM的和训练脚本，支持本地训练。新增ChatAgent,实现各种有实际场景价值的Agent实现。

    Tagged pytorchPython

    3.6K

  • NVIDIA/TransformerEngine

    A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.

    Tagged pytorchPython

    3.6K

  • foolwood/SiamMask

    [CVPR19/TPAMI23] SiamMask: A Framework for Fast Online Object Tracking and Segmentation

    Tagged pytorchPython

    3.6K

  • jmschrei/pomegranate

    Fast, flexible and easy to use probabilistic modelling in Python.

    Tagged pytorchPython

    3.5K

  • microsoft/hummingbird

    Hummingbird compiles trained ML models into tensor computation for faster inference.

    Tagged pytorchPython

    3.5K

  • cszn/KAIR

    Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

    Tagged pytorchPython

    3.5K

  • podgorskiy/ALAE

    [CVPR2020] Adversarial Latent Autoencoders

    Tagged pytorchPython

    3.5K

  • zjhellofss/KuiperInfer

    校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

    Tagged pytorchC++

    3.5K

  • huggingface/optimum

    🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

    Tagged pytorchPython

    3.5K

  • kuprel/min-dalle

    min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch

    Tagged pytorchPython

    3.5K

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

    Listed in the catalogPyPI

    Not published by PyPI

Ecosystem 582packages that depend on it, most-adopted first

  • lmms-eval

    A framework for evaluating large multi-modality language models

    Depends on torchPyPI

    Not published by PyPI
  • local-attention

    Local attention, window with lookback, for language modeling

    Depends on torchPyPI

    Not published by PyPI
  • lovely-tensors

    ❤️ Lovely Tensors

    Depends on torchPyPI

    Not published by PyPI
  • lpips

    LPIPS Similarity metric

    Depends on torchPyPI

    Not published by PyPI
  • lsglang

    SGLang is a fast serving framework for large language models and vision language models.

    Depends on torchPyPI

    Not published by PyPI
  • lycoris-lora

    Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion

    Depends on torchPyPI

    Not published by PyPI
  • mace-torch

    Depends on torchPyPI

    Not published by PyPI
  • magic-pdf

    A practical tool for converting PDF to Markdown

    Depends on torchPyPI

    Not published by PyPI
  • magic123

    Magic123: one image to high-quality 3D object generation using 2D and 3D diffusion priors.

    Depends on torchPyPI

    Not published by PyPI
  • make-a-video-pytorch

    Make-A-Video - Pytorch

    Depends on torchPyPI

    Not published by PyPI
  • mamba-ssm

    Mamba state-space model

    Depends on torchPyPI

    Not published by PyPI
  • mambapy

    A simple and efficient Mamba implementation in pure PyTorch.

    Depends on torchPyPI

    Not published by PyPI

Latest news the 3 latest events that mention it