Hugging Face Transformers Documentation
by Hugging Face
The de facto standard library for using pretrained models — thousands of them, one API.
Overview
Transformers is the library that put hundreds of thousands of pretrained models one line of code away. Its documentation teaches the pipeline API for quick inference, the Auto classes for loading any model/tokenizer, generation configuration, and fine-tuning — across text, vision, audio, and multimodal tasks. It's essential reference knowledge for anyone working with open models.
At a Glance
- Topic
- Frameworks
- Level
- Intermediate
- Format
- Documentation
- Cost
- Free
- Duration
- Self-paced
- Provider
- Hugging Face
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓Running inference with pipelines
- ✓Loading any model with Auto classes
- ✓Text generation configuration
- ✓Fine-tuning and sharing models on the Hub
Highlights
- •Access to hundreds of thousands of models
- •Text, vision, audio, and multimodal
Who It’s For
Best For
- ✓Developers working with open pretrained models
Prerequisites
- •Python
- •PyTorch basics helpful
FAQ
What is Hugging Face Transformers Documentation?
Official docs for the Transformers library, the standard way to download, run, and fine-tune pretrained models across modalities.
Is Hugging Face Transformers Documentation free?
Hugging Face Transformers Documentation is free to access.
What level is Hugging Face Transformers Documentation for?
Hugging Face Transformers Documentation is aimed at a intermediate audience. Recommended background: Python, PyTorch basics helpful.
How long does Hugging Face Transformers Documentation take?
Expect roughly Self-paced. Most learners work through it at their own pace.
What will I learn from Hugging Face Transformers Documentation?
You'll learn: Running inference with pipelines; Loading any model with Auto classes; Text generation configuration; Fine-tuning and sharing models on the Hub.