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
- potamides/DeTikZify
Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ.
1.8K stars
- zai-org/CogView
Text-to-Image generation. The repo for NeurIPS 2021 paper "CogView: Mastering Text-to-Image Generation via Transformers".
1.8K stars
- lihanghang/NLP-Knowledge-Graph
自然语言处理、知识图谱、对话系统，大模型等技术研究与应用。
1.8K stars
- lucidrains/alphafold3-pytorch
Implementation of Alphafold 3 from Google Deepmind in Pytorch
1.7K stars
- nyu-mll/jiant
jiant is an nlp toolkit
1.7K stars
- invictus717/MetaTransformer
Meta-Transformer for Unified Multimodal Learning
1.6K stars
- intel/auto-round
A simple and effective post training quantization toolkit for high-accuracy low-bit LLM inference|简洁且高效的后训练量化工具包
1.6K stars
- PKU-Alignment/safe-rlhf
Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback
1.6K stars
- autonomousvision/transfuser
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
1.6K stars
- SalesforceAIResearch/uni2ts
Unified Training of Universal Time Series Forecasting Transformers
1.6K stars
- time-series-foundation-models/lag-llama
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
1.6K stars
- FoundationVision/Infinity
[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis
1.6K 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
- mambavision
MambaVision: A Hybrid Mamba-Transformer Vision Backbone
Not published by PyPI - manga-ocr
OCR for Japanese manga
Not published by PyPI - marker-pdf
Convert documents to markdown with high speed and accuracy.
Not published by PyPI - markllm
MarkLLM: An Open-Source Toolkit for LLM Watermarking
Not published by PyPI - mechbench-compute
Composable mechanistic-interpretability primitives: hook-aware forward, interventions, activation cache, logit lens, probes, and geometry.
Not published by PyPI - megatts
MegaTTS 3 - A lightweight and efficient TTS system with ultra high-quality voice cloning
Not published by PyPI - memoryos
Intelligence Begins with Memory
Not published by PyPI - minference
To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention, which reduces inference latency by up to 10x for pre-filling on an A100 while maintaining accuracy.
Not published by PyPI - mlx-audio
MLX-Audio is a package for inference of text-to-speech (TTS) and speech-to-speech (STS) models locally on your Mac using MLX
Not published by PyPI - mlx-lm
LLMs with MLX and the Hugging Face Hub
Not published by PyPI - mlx-tune
MLX-powered LLM/VLM/TTS/STT/Embedding/OCR/JEPA fine-tuning for Apple Silicon - Unsloth-compatible API for Mac
Not published by PyPI - mlx-vlm
MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) and Omni Models (VLMs with audio and video support) on your Mac using MLX.
Not published by PyPI
Latest news the 2 latest events that mention it
- 33d agoSEP 22, 2026
- 4mo agoJUL 8, 2026