Instructions to use fimu-docproc-research/xlm-roberta-large-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fimu-docproc-research/xlm-roberta-large-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fimu-docproc-research/xlm-roberta-large-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fimu-docproc-research/xlm-roberta-large-ner") model = AutoModelForTokenClassification.from_pretrained("fimu-docproc-research/xlm-roberta-large-ner") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
The finetuned XLM-RoBERTa (large-sized model) for Named Entity Recognition
This model was finetuned on the Czech invoice dataset.
Achieved results:
eval_accuracy = 0.9618613
eval_f1 = 0.7825681
eval_precision = 0.7752081
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