osiria/distiluse-base-italian

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    Model: DistilUSE
    Lang: IT
  
 

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Model description

This is a Universal Sentence Encoder [1] model for the Italian language, obtained using mDistilUSE (distiluse-base-multilingual-cased-v1) as a starting point and focusing it on the Italian language by modifying the embedding layer (as in [2], computing document-level frequencies over the Wikipedia dataset)

The resulting model has 67M parameters, a vocabulary of 30.785 tokens, and a size of ~270 MB.

It can be used to encode Italian texts and compute similarities between them.

Quick usage

from transformers import AutoTokenizer, AutoModel
import numpy as np

tokenizer = AutoTokenizer.from_pretrained("osiria/distiluse-base-italian")
model = AutoModel.from_pretrained("osiria/distiluse-base-italian")

text1 = "Alessandro Manzoni è stato uno scrittore italiano"
text2 = "Giacomo Leopardi è stato un poeta italiano"

vec1 = model(tokenizer.encode(text1, return_tensors = "pt")).last_hidden_state[0,0,:].cpu().detach().numpy()
vec2 = model(tokenizer.encode(text2, return_tensors = "pt")).last_hidden_state[0,0,:].cpu().detach().numpy()

cosine_similarity = np.dot(vec1, vec2)/(np.linalg.norm(vec1)*np.linalg.norm(vec2))
print("COSINE SIMILARITY:", cosine_similarity)

# COSINE SIMILARITY: 0.734292

References

[1] https://arxiv.org/abs/1907.04307

[2] https://arxiv.org/abs/2010.05609

License

The model is released under Apache-2.0 license