Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use embaas/sentence-transformers-multilingual-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use embaas/sentence-transformers-multilingual-e5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("embaas/sentence-transformers-multilingual-e5-large") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Inquiry About the Details of Your Model
#1
by esudedogan - opened
Hello,
I couldn't find detailed information about your model on your page. Apart from being a Sentence Transformers model, is there any difference between your model and the e5 multilingual large model? I would appreciate it if you could provide an explanation about your model.
Best regards.