Instructions to use acayir64/turkish-embedding-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use acayir64/turkish-embedding-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("acayir64/turkish-embedding-model") 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
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Verified signature## Sample usage from sentence_transformers import SentenceTransformer model = SentenceTransformer("acayir64/turkish-embedding-model") sentences = [ "Ali ata bak.", "Ata bak kim gelmiş!", "Ata bak Ali!", ] embeddings = model.encode(sentences) print(embeddings.shape) [3, 384] similarities = model.similarity(embeddings, embeddings) print(similarities)bcf1a81 -
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