Technology · Library
Transformers
Library · Hugging Face · Catalog tech@1
Hugging Face's library of pretrained models.
- Matched as
- hugging face transformers
- transformers
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. Transformers 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.166,907 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 1.0 in the last 30 days · 1 in the 30 before
Adoption by registry
The growth of Transformers’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 Transformers’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
- 0published events that mention it
- Events · 30 days
- 0published events that mention it
- Previous 30 days
- 1events 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
- huggingface/transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
166.9K stars
Members 140repositories tagged with one of its aliases, most-starred first
- yeyupiaoling/Whisper-Finetune
Fine-tune the Whisper speech recognition model to support training without timestamp data, training with timestamp data, and training without speech data. Accelerate inference and support Web deployment, Windows desktop deployment, and Android deployment
1.2K stars
- The-AI-Summer/self-attention-cv
Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.
1.2K stars
- openvinotoolkit/nncf
Neural Network Compression Framework for enhanced OpenVINO™ inference
1.2K stars
- lucidrains/CoCa-pytorch
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch
1.2K stars
- bodaay/HuggingFaceModelDownloader
Simple go utility to download HuggingFace Models and Datasets
1.2K stars
- lucidrains/performer-pytorch
An implementation of Performer, a linear attention-based transformer, in Pytorch
1.2K stars
- MediaBrain-SJTU/MING
明医 (MING)：中文医疗问诊大模型
1.2K stars
- SuperBruceJia/EEG-DL
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
1.2K stars
- Rizzo-AI-Academy/rizzo-pii
Local-first privacy guard: anonymize your documents before sharing with LLMs.
1.1K stars
- datadreamer-dev/DataDreamer
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models. 🤖💤
1.1K stars
- gordicaleksa/pytorch-original-transformer
My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT pretrained models.
1.1K stars
- snap-research/EfficientFormer
EfficientFormerV2 [ICCV 2023] & EfficientFormer [NeurIPs 2022]
1.1K stars
Packages
“Is” packages are Transformers 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 11the technology itself, most-adopted first
- divyanx-transformers
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - mcwtransformers
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - my-transformers
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - rlinf-transformer-openpi
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - t-draft-123
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - transformers
Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Not published by PyPI - transformers-kt
Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Not published by PyPI - transformers-mcw
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - transformers-openpi
State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow
Not published by PyPI - transformers-qwenomni
Transformers: With code for Qwen 2.5 Omni
Not published by PyPI - transformers-usf-om-vl-exp-v0
Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Not published by PyPI
Ecosystem 279packages that depend on it, most-adopted first
- xtest-bert-score
PyTorch implementation of BERT score for xtest
Not published by PyPI - xtuner
An efficient, flexible and full-featured toolkit for fine-tuning large models
Not published by PyPI - zimage-mnn
Z-Image-Turbo text-to-image generation on MNN (Apple Silicon Metal / CPU)
Not published by PyPI
Latest news the 2 latest events that mention it
- 32d agoSEP 22, 2026
- 4mo agoJUL 8, 2026