Question 1

How do I set up a basic Hungarian NLP pipeline in Python?

Accepted Answer

Start with tokenization using huntoken or HuSpaCy, add morphological analysis with emMorphPy, and leverage pre-trained models like huBERT from the Language Models section. The README provides links to these tools but no step-by-step integration guide.

Question 2

What's the best Hungarian language model for text classification?

Accepted Answer

Models like huBERT and PULI-BERT-Large are listed for transformer-based tasks, and for sentiment analysis, SentimentAnalysisHUN is a dedicated tool. However, no performance comparisons are provided, so experimentation is needed.

Question 3

HuSpaCy or magyarlanc: which should I use for a production project?

Accepted Answer

HuSpaCy is designed for industrial-strength processing with spaCy integration and commercial licenses, while magyarlanc is a toolkit for basic linguistic tasks. HuSpaCy is better for modern Python pipelines, but check specific requirements and licenses.

Question 4

Where can I find large Hungarian text corpora for training language models?

Accepted Answer

The Raw Corpora section lists resources like the Hungarian Webcorpus 2.0 with over 9 billion words and OSCAR with 2339 million unique words, available under open licenses for download and use.

Question 5

Are there Hungarian LLMs that support fine-tuning for custom tasks?

Accepted Answer

Yes, models like PULI-GPTrio and SambaLingo-Hungarian-Base are available on Hugging Face, as mentioned in the Large Language Models section, and can be fine-tuned using standard frameworks.

Question 6

How does Hungarian NLP tooling compare to English in terms of availability?

Accepted Answer

Hungarian has fewer dedicated tools than English, but this directory aggregates specialized resources like HuSpaCy and unique datasets, though they may lack the polish and community support of English-centric libraries like NLTK or spaCy.

awesome-hungarian-nlp

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