# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("LHF/eu-sts")
model = AutoModelForSequenceClassification.from_pretrained("LHF/eu-sts")Quick Links
Basque Semantic Textual Similarity Model
import transformers
if __name__ == '__main__':
model = 'eu-sts'
tokenizer = transformers.AutoTokenizer.from_pretrained(model)
model = transformers.BertForSequenceClassification.from_pretrained(model)
sentence_pairs = [("Nire ama etxera etorri da.", "Ama visitan etorri da etxera")]
for sp in sentence_pairs:
result = model(**tokenizer(*sp, return_tensors='pt'))
print(sp, result.logits)
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LHF/eu-sts")