Instructions to use MMG/xlm-roberta-large-ner-spanish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMG/xlm-roberta-large-ner-spanish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MMG/xlm-roberta-large-ner-spanish")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MMG/xlm-roberta-large-ner-spanish") model = AutoModelForTokenClassification.from_pretrained("MMG/xlm-roberta-large-ner-spanish") - Inference
- Notebooks
- Google Colab
- Kaggle
xlm-roberta-large-ner-spanish
This model is a XLM-Roberta-large model fine-tuned for Named Entity Recognition (NER) over the Spanish portion of the CoNLL-2002 dataset. Evaluating it over the test subset of this dataset, we get a F1-score of 89.17, being one of the best NER for Spanish available at the moment.
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