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
- lucidrains/musiclm-pytorch
Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
3.3K stars
- lucasjinreal/yolov7_d2
🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
3.1K stars
- linto-ai/whisper-timestamped
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
2.9K stars
- adapter-hub/adapters
A Unified Library for Parameter-Efficient and Modular Transfer Learning
2.8K stars
- kha-white/manga-ocr
Optical character recognition for Japanese text, with the main focus being Japanese manga
2.8K stars
- saharmor/dalle-playground
A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini)
2.7K stars
- roboflow/maestro
streamline the fine-tuning process for multimodal models: PaliGemma 2, Florence-2, and Qwen2.5-VL
2.7K stars
- lucidrains/audiolm-pytorch
Implementation of AudioLM, a SOTA Language Modeling Approach to Audio Generation out of Google Research, in Pytorch
2.6K stars
- mflux-community/mflux
Apple MLX native implementations of state-of-the-art generative image & video models
2.4K stars
- nz-m/SocialEcho
Social networking platform with automated content moderation and context-based authentication system
2.4K stars
- refuel-ai/autolabel
Label, clean and enrich text datasets with LLMs.
2.3K stars
- buaacyw/MeshAnything
[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
2.3K 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
- 33d agoSEP 22, 2026
- 4mo agoJUL 8, 2026