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cross-encoder-umberto-stsb
efederici/cross-encoder-umberto-stsb
cross-encoder-umberto-stsb is a text classification model from efederici. Use it when you need a label for a piece of text. It is set up for transformers.
This model was trained using SentenceTransformers Cross-Encoder class.
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Apr 4, 2022
- Updated
- Apr 4, 2022
- SHA
- 7fa457e8
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Datasets
Model card
From the Hugging Face model README
Cross-Encoder
This model was trained using SentenceTransformers Cross-Encoder class.
<p align="center"> <img src="https://user-images.githubusercontent.com/7140210/72913702-d55a8480-3d3d-11ea-99fc-f2ef29af4e72.jpg" width="700"> </br> Marco Lodola, Monument to Umberto Eco, Alessandria 2019 </p>Training Data
This model was trained on stsb. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.
Usage and Performance
from sentence_transformers import CrossEncoder
model = CrossEncoder('efederici/cross-encoder-umberto-stsb')
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').
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Languages
- it
- Created
- Apr 4, 2022
- Updated
- Apr 4, 2022