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
- Xet hash:
- b3e6bf0d72c896304bc0a6151775c8c29927657f3520b4c6923d6a128a0f2047
- Size of remote file:
- 16.8 MB
- SHA256:
- 0c16d8a2bff758ba6e009849c31b8ffc8ba92bfc907e0bcee96a09f1818fe2da
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