Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:800
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Nada-10/multilingual-e5-small-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Nada-10/multilingual-e5-small-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Nada-10/multilingual-e5-small-finetuned") sentences = [ "Can you provide the definition of deaerating chamber?", "冷却水中に含まれる泥砂を沈澱させる池。", "脱気室の上部にあって、溶存ガスを分離する室。", "制御系の状態を変えようとする外的作用。" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K