Instructions to use mercelisw/xlm-roberta-base-extended-language-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mercelisw/xlm-roberta-base-extended-language-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mercelisw/xlm-roberta-base-extended-language-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mercelisw/xlm-roberta-base-extended-language-detection") model = AutoModelForSequenceClassification.from_pretrained("mercelisw/xlm-roberta-base-extended-language-detection") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
languages: - la - grc - he
This model builds upon an existing language detection model. It uses the same dataset, extended with Latin, Ancient Greek and (modern) Hebrew texts.
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