# 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", device_map="auto")Quick Links
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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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nielsr/lilt-xlm-roberta-base")