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---
library_name: transformers
datasets:
- umarigan/all_nli_tr
language:
- tr
pipeline_tag: sentence-similarity
---
# Model Card for Model ID
```bash
pip install -U sentence-transformers
```
Load the model and run inference.
```python
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]
```
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