Sentence Similarity
sentence-transformers
Safetensors
Russian
English
multilingual
xlm-roberta
feature-extraction
mteb
e5
contrastive-learning
text-embeddings-inference
Instructions to use olegGerbylev/multilingual-e5-large-finetuned-orders with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use olegGerbylev/multilingual-e5-large-finetuned-orders with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("olegGerbylev/multilingual-e5-large-finetuned-orders") sentences = [ "Это счастливый человек", "Это счастливая собака", "Это очень счастливый человек", "Сегодня солнечный день" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 283 Bytes
731584e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"model_type": "SentenceTransformer",
"__version__": {
"sentence_transformers": "5.2.2",
"transformers": "5.0.0",
"pytorch": "2.10.0+cu128"
},
"prompts": {
"query": "",
"document": ""
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |