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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 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
- davidtvs/pytorch-lr-finder
A learning rate range test implementation in PyTorch
1K stars
- NATSpeech/NATSpeech
A Non-Autoregressive Text-to-Speech (NAR-TTS) framework, including official PyTorch implementation of PortaSpeech (NeurIPS 2021) and DiffSpeech (AAAI 2022)
1K 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
- efficientnet-pytorch-youngj98
EfficientNet implemented in PyTorch.
Not published by PyPI - efficientvit-gml
open-set object detector
Not published by PyPI - ema-pytorch
Easy way to keep track of exponential moving average version of your pytorch module
Not published by PyPI - emotivoice
EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine
Not published by PyPI - entmax
The entmax mapping and its loss, a family of sparse alternatives to softmax.
Not published by PyPI - espnet
ESPnet: end-to-end speech processing toolkit
Not published by PyPI - espnet-s3prl
Self-Supervised Speech Pre-training and Representation Learning Toolkit (ESPnet fork)
Not published by PyPI - evotorch
EvoTorch is an advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
Not published by PyPI - evox
evox
Not published by PyPI - f5-tts
F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching
Not published by PyPI - fa3-fwd
FlashAttention-3 forward
Not published by PyPI - fa4
Flash Attention CUTE (CUDA Template Engine) implementation
Not published by PyPI
Latest news the 3 latest events that mention it
- 15h agoOCT 24, 2026
- 2d agoOCT 22, 2026
- 4mo agoJUL 10, 2026