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 signals

No 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.

    Official repositoryPython

    166.9K stars

Members 140repositories tagged with one of its aliases, most-starred first

  • hiyouga/LlamaFactory

    Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

    Tagged transformersPython

    75.3K stars

  • labmlai/annotated_deep_learning_paper_implementations

    🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

    Tagged transformersPython

    67.5K stars

  • lucidrains/vit-pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

    Tagged transformersPython

    25.5K stars

  • amusi/CVPR2026-Papers-with-Code

    CVPR 2026 论文和开源项目合集

    Tagged transformers

    22.9K stars

  • huggingface/peft

    🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

    Tagged transformersPython

    21.7K stars

  • stas00/ml-engineering

    Machine Learning Engineering Open Book

    Tagged transformersPython

    19.1K stars

  • arc53/DocsGPT

    Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.

    Tagged transformersPython

    18.3K stars

  • NVIDIA/Megatron-LM

    Ongoing research training transformer models at scale

    Tagged transformersPython

    18.1K stars

  • huggingface/transformers.js

    State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!

    Tagged transformersJavaScript

    16.3K stars

  • BlinkDL/RWKV-LM

    RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

    Tagged transformersPython

    14.7K stars

  • neuml/txtai

    💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows

    Tagged transformersPython

    13K stars

  • PaddlePaddle/PaddleNLP

    Easy-to-use and powerful LLM and SLM library with awesome model zoo.

    Tagged transformersPython

    13K 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

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • mcwtransformers

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • my-transformers

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • rlinf-transformer-openpi

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • t-draft-123

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    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.

    Listed in the catalogPyPI

    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.

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • transformers-mcw

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • transformers-openpi

    State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow

    Published from huggingface/transformersPyPI

    Not published by PyPI
  • transformers-qwenomni

    Transformers: With code for Qwen 2.5 Omni

    Published from huggingface/transformersPyPI

    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.

    Published from huggingface/transformersPyPI

    Not published by PyPI

Ecosystem 279packages that depend on it, most-adopted first

  • adapters

    A Unified Library for Parameter-Efficient and Modular Transfer Learning

    Depends on transformersPyPI

    Not published by PyPI
  • adaptive-classifier

    A flexible, adaptive classification system for dynamic text classification

    Depends on transformersPyPI

    Not published by PyPI
  • ai-dynamo-vllm

    A high-throughput and memory-efficient inference and serving engine for LLMs

    Depends on transformersPyPI

    Not published by PyPI
  • aiconfig-extension-hugging-face

    An extension for using Hugging Face tasks to parse models for AIConfig.

    Depends on transformersPyPI

    Not published by PyPI
  • aiconfig-extension-llama-guard

    An extension for using LLama Guard with aiconfig

    Depends on transformersPyPI

    Not published by PyPI
  • aideml

    Autonomous AI for Data Science and Machine Learning

    Depends on transformersPyPI

    Not published by PyPI
  • aiperf

    AIPerf is a package for performance testing of AI models

    Depends on transformersPyPI

    Not published by PyPI
  • airllm

    AirLLM runs 70B large language models on a single 4GB GPU without quantization, distillation or pruning. Kimi K3 2.8T on under 4GB, Qwen3.8-Flash-Next 125B on 6GB, DeepSeek-V3 671B on ~12GB. Train Qwen3.8-Flash-Next under 6GB.

    Depends on transformersPyPI

    Not published by PyPI
  • alibi

    Algorithms for monitoring and explaining machine learning models

    Depends on transformersPyPI

    Not published by PyPI
  • alibi-detect

    Algorithms for outlier detection, concept drift and metrics.

    Depends on transformersPyPI

    Not published by PyPI
  • alphafold3-pytorch

    Alphafold 3 - Pytorch

    Depends on transformersPyPI

    Not published by PyPI
  • amd-gaia

    GAIA is a lightweight agent framework designed for the edge and AI PCs.

    Depends on transformersPyPI

    Not published by PyPI

Latest news the 2 latest events that mention it

Transformers · Library — Crest of Tech