NielsRogge/Transformers-Tutorials resource

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11748 stars · 1736 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A collection of Jupyter notebook tutorials demonstrating how to use the HuggingFace Transformers library with PyTorch. It covers fine-tuning and inference for many transformer models across NLP, vision, and audio tasks.

Use cases

• learn how to fine-tune BERT for named entity recognition
• tutorial for multi-label text classification with transformers
• run inference with vision transformer models
• fine-tune GPT-2 on custom text
• understand HuggingFace transformers library with examples
• classify audio with the audio spectrogram transformer
• learn document understanding with LayoutLM

When to choose

• you want hands-on notebook examples for HuggingFace Transformers models
• you need reference code for fine-tuning transformer models in PyTorch
• you are learning NLP, vision, or audio tasks with pretrained transformers

When to avoid

• you need a production-ready library rather than educational notebooks
• you use TensorFlow instead of PyTorch
• you want a structured course rather than standalone demos

Facets

learning-resource · maturity active

machine-learning deep-learning nlp computer-vision transformers deep-learning computer-vision tutorials large-language-models python jvm huggingface jupyter-notebooks pytorch transformers tutorials fine-tuning bert gpt-2 vision-transformer layoutlm natural-language-processing

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