Sentence Similarity
sentence-transformers
PyTorch
multilingual
xlm-roberta
nutrition
retrieval
text-embeddings-inference
Instructions to use linhha2705/multilingual-e5-simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use linhha2705/multilingual-e5-simple with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("linhha2705/multilingual-e5-simple") 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
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- best_model.safetensors +3 -0
- model.safetensors +3 -0
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