Sentence Similarity
sentence-transformers
Safetensors
Turkish
xlm-roberta
feature-extraction
embeddings
turkish
türkçe
e5
retrieval
semantic-search
mteb
tr-mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use thealper2/intfloat-multilingual-e5-base-tr-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thealper2/intfloat-multilingual-e5-base-tr-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thealper2/intfloat-multilingual-e5-base-tr-nli") 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
File size: 283 Bytes
cf90e06 | 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": "2.11.0+cu128"
},
"prompts": {
"query": "",
"document": ""
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |