Instructions to use nielsr/lilt-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/lilt-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nielsr/lilt-xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nielsr/lilt-xlm-roberta-base") model = AutoModel.from_pretrained("nielsr/lilt-xlm-roberta-base") - Inference
- Notebooks
- Google Colab
- Kaggle
LiLT + XLM-RoBERTa-base
This model is created by combining the Language-Independent Layout Transformer (LiLT) with XLM-RoBERTa, a multilingual RoBERTa model (trained on 100 languages).
This way, we have a LayoutLM-like model for 100 languages :)
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