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
| { | |
| "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" | |
| } |