Instructions to use scampion/eubert_cross-encoder_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scampion/eubert_cross-encoder_v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("scampion/eubert_cross-encoder_v1") model = AutoModel.from_pretrained("scampion/eubert_cross-encoder_v1") - Notebooks
- Google Colab
- Kaggle
EUBERT Cross-Encoder
EUBERT MLM finetuned as cross-encoder for the 24 languages of 🇪🇺 via the sentence-transformers training set: https://sbert.net/datasets/AllNLI.tsv.gz
from sentence_transformers import CrossEncoder
model = CrossEncoder('EuropeanParliament/eubert_cross-encoder_v1', max_length=512)
scores = model.predict([('Query', 'Paragraph1'), ('Query', 'Paragraph2') , ('Query', 'Paragraph3')])
Author:
- Sébastien Campion sebastien.campion@europarl.europa.eu
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