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cross-encoder-italian-bert-stsb
nickprock/cross-encoder-italian-bert-stsb
cross-encoder-italian-bert-stsb is a text ranking model from nickprock. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for sentence-transformers. The card lists the license as mit.
This model was trained using SentenceTransformers Cross-Encoder class. The original model is dbmdz/bert-base-italian-uncased.
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Model card
From the Hugging Face model README
Cross-Encoder for STSB-Multi
This model was trained using SentenceTransformers Cross-Encoder class. The original model is dbmdz/bert-base-italian-uncased.
Training Data
This model was trained on the STS benchmark dataset, in particular the italian translation. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.
Usage and Performance
Pre-trained models can be used like this:
from sentence_transformers import CrossEncoder
model = CrossEncoder('model_name')
scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])
The model will predict scores for the pairs ('Sentence 1', 'Sentence 2') and ('Sentence 3', 'Sentence 4').
You can use this model also without sentence_transformers and by just using Transformers AutoModel class
- Task
- Text Ranking
- Library
- sentence-transformers
- Type
- bert
- License
- mit
- Languages
- it
- Created
- May 10, 2023
- Updated
- Apr 4, 2025