Instructions to use tner/xlm-roberta-base-uncased-conll2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tner/xlm-roberta-base-uncased-conll2003 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tner/xlm-roberta-base-uncased-conll2003")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tner/xlm-roberta-base-uncased-conll2003") model = AutoModelForTokenClassification.from_pretrained("tner/xlm-roberta-base-uncased-conll2003") - Notebooks
- Google Colab
- Kaggle
| {"valid": {"f1": 20.42755344418052, "recall": 16.538461538461537, "precision": 26.70807453416149, "summary": " precision recall f1-score support\n\n entity 0.27 0.17 0.20 260\n\n micro avg 0.27 0.17 0.20 260\n macro avg 0.27 0.17 0.20 260\nweighted avg 0.27 0.17 0.20 260\n"}} |