nlp-with-transformers/notebooks resource

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4800 stars · 1477 forks observed · 2026-08-28

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

A collection of Jupyter notebooks containing the example code from the O'Reilly book 'Natural Language Processing with Transformers'. The notebooks cover transformer-based NLP tasks and are designed to run on GPU-enabled cloud platforms like Colab or locally.

Use cases

• learn how to fine-tune transformer models for NLP tasks
• follow along with the NLP with Transformers book exercises
• get runnable examples of Hugging Face Transformers in PyTorch
• study named entity recognition, question answering, and text classification with transformers
• practice NLP on Google Colab with GPU support

When to choose

• you are reading the book and want the accompanying code
• you want hands-on, chapter-by-chapter transformer tutorials
• you prefer PyTorch-based examples with cloud notebook support

When to avoid

• you need the TensorFlow code paths, which are no longer tested
• you want a maintained question-answering chapter, which relies on deprecated Haystack 0.9/1.4 and Elasticsearch 7.x
• you need production-ready code rather than educational examples

Facets

learning-resource · maturity active

nlp machine-learning llm-training rag deep-learning tutorials large-language-models python cross-platform jupyter-notebooks huggingface-transformers pytorch book-examples education natural-language-processing gpu

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