Sentence Similarity
sentence-transformers
PyTorch
multilingual
distilbert
DistilBert
Universal Sentence Encoder
sentence-embeddings
Instructions to use sadakmed/distiluse-base-multilingual-cased-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sadakmed/distiluse-base-multilingual-cased-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sadakmed/distiluse-base-multilingual-cased-v2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
While v1 model supports 15 languages, this version supports 50+ languages. However, performance on the 15 languages mentioned in v1 are reported to be a bit lower.
Note that ST has additional two layers(Pooling, Linear), that cannot be saved in any predefined model in HG.
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