// devtools · huggingface/transformers

Transformers

Transformers é um projeto de ferramentas de desenvolvimento de código aberto de huggingface (huggingface/transformers no GitHub). Tem 166.942 estrelas no GitHub e 34.748 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 4 de outubro de 2026.

The model-definition framework behind modern AI — thousands of pretrained transformers for text, vision, and audio.

★ 166,9 mil estrelas⑂ 34,7 mil forksApache-2.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Estrelas no GitHub
166.942
Forks
34.748
Licença
Apache-2.0
Última atualização no GitHub
4 de outubro de 2026
Tipo de ficha
Guia de instalação completo
Site oficial
Official docs
// como funciona

Como funciona

  1. Pick a task

    Text, image, audio, or multimodal — find the pipeline that matches what you want to build.

  2. Load a model

    One line downloads a pretrained checkpoint from the Hugging Face Hub.

  3. Run it

    Call the pipeline on your input; batching and device placement are handled for you.

  4. Fine-tune or deploy

    Use the Trainer API for custom training, then export for serving.

// recursos

Por que as pessoas gostam tanto

Thousands of models

One API across BERT, GPT, Llama, Whisper, ViT, and thousands more — swap checkpoints without rewriting code.

Pipelines API

Task-based one-liners for classification, generation, transcription, and vision — from prototype to demo in minutes.

Framework agnostic

PyTorch, TensorFlow, and JAX backends; export to ONNX and TorchScript for production serving.

Trainer

A full training loop with mixed precision, distributed training, and experiment tracking built in.

Tokenizers

Blazing-fast Rust tokenizers with Python bindings — correct encoding for every model family.

Ecosystem gravity

The default dependency of the open AI world: tutorials, integrations, and answers for everything.

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// execute você mesmo

Execute você mesmo

  1. Step 1 — Install

    Pip-install the library plus your framework of choice.

    pip install transformers torch
  2. Step 2 — Pick a pipeline

    Choose the task; the docs list every supported pipeline with examples.

    from transformers import pipeline
  3. Step 3 — Generate

    Load any Hub model by name and run it locally or on your GPU.

    pipe = pipeline('summarization'); print(pipe(long_text))
// casos de uso

O que você pode criar

From the tooling end of the shelf, Pacwich handles monorepos that run on bun and pnpm — the unglamorous plumbing larger projects end up needing. Readers working through the Dev Tools shelf also stop at @shadcn/lint, an agent-first linter for Tailwind design systems: you define what is allowed, and errors explain the fix in terms of your components. Also on this shelf: phoenix — a code editor designed to make coding as fun as playing a video game.

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// perguntas frequentes

Perguntas frequentes

Who maintains Transformers?

It is an open-source project at huggingface/transformers with 34,742 forks. Check the repo's contributors and recent commits to see how active maintenance is.

Is Transformers free for commercial use?

Yes — Apache-2.0. Individual model checkpoints carry their own licenses, so check each one.

Do I need a GPU?

Inference on small models works on CPU; training and large models want a GPU.

PyTorch or TensorFlow?

Both are supported; PyTorch is the community default today.

Where do the models come from?

The Hugging Face Hub hosts hundreds of thousands of checkpoints loadable by name.

// continue explorando

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// alternativas

Alternativas em Ferramentas de desenvolvimento

Os outros projetos de Ferramentas de desenvolvimento com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se Transformers não for o ideal para você.

// mais em devtools

Mais em Ferramentas de desenvolvimento

Projetos de Ferramentas de desenvolvimento próximos no catálogo, os mais próximos em estrelas de Transformers: continue explorando dos dois lados dele.

Baixe o Transformers

Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.