metadata

library_name: transformers
datasets:
  - umarigan/all_nli_tr
language:
  - tr
pipeline_tag: sentence-similarity

Model Card for Model ID

pip install -U sentence-transformers

Load the model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("umarigan/distilbert-turkish-sentence-similarity")
# Run inference
sentences = [
    'Bu yıl tatile Antalya'ya gideceğiz.',
    'Yazın Antalya'da tatil yapacağız.'
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [2, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [2, 2]