Technology · Framework
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
- ZhaoJ9014/face.evoLVe
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
3.6K stars
- pytorch/rl
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
3.6K stars
- 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。
3.6K stars
- 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.
3.6K stars
- foolwood/SiamMask
[CVPR19/TPAMI23] SiamMask: A Framework for Fast Online Object Tracking and Segmentation
3.6K stars
- jmschrei/pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
3.5K stars
- microsoft/hummingbird
Hummingbird compiles trained ML models into tensor computation for faster inference.
3.5K stars
- cszn/KAIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
3.5K stars
- podgorskiy/ALAE
[CVPR2020] Adversarial Latent Autoencoders
3.5K stars
- 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
3.5K stars
- huggingface/optimum
🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
3.5K stars
- kuprel/min-dalle
min(DALL·E) is a fast, minimal port of DALL·E Mini to PyTorch
3.5K 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
- vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - vllm-acc
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - vllm-ascend
vLLM Ascend backend plugin
Not published by PyPI - vllm-cpu
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - vllm-cpu-amxbf16
vLLM CPU inference engine (AVX512 + VNNI + BF16 + AMX optimized)
Not published by PyPI - vllm-cpu-avx512
vLLM CPU inference engine (AVX512 optimized)
Not published by PyPI - vllm-cpu-avx512bf16
vLLM CPU inference engine (AVX512 + VNNI + BF16 optimized)
Not published by PyPI - vllm-cpu-nightly
A high-throughput and memory-efficient inference and serving engine for LLMs
Not published by PyPI - vocos
Fourier-based neural vocoder for high-quality audio synthesis
Not published by PyPI - voicefixer
This package is written for the restoration of degraded speech
Not published by PyPI - voxcpm
VoxCPM: Tokenizer-Free TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning
Not published by PyPI - voxelmorph
Unsupervised Learning for Image Registration.
Not published by PyPI
Latest news the 3 latest events that mention it
- 28h agoOCT 24, 2026
- 3d agoOCT 22, 2026
- 4mo agoJUL 10, 2026