---
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]
```