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library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- dense
- arabic
---
# NeoAraBERT-STS
Sentence-transformers model for Arabic semantic textual similarity.
## Usage
```bash
pip install -U sentence-transformers torch
```
```python
import torch
from sentence_transformers import SentenceTransformer
model_name = "U4RASD/NeoAraBERT-STS"
finetuned_model = SentenceTransformer(
model_name,
model_kwargs={"trust_remote_code": True, "torch_dtype": torch.float32},
tokenizer_kwargs={"trust_remote_code": True},
config_kwargs={"trust_remote_code": True},
)
finetuned_model.max_seq_length = 512
sentences = [
"التقارير بدأت تصل في وقت متأخر من هذا العام ويتم مراجعتها",
"يتم مراجعة التقارير في أواخر هذا العام.",
"لم يكن هناك تقارير هذا العام على الإطلاق.",
]
embeddings = finetuned_model.encode(sentences)
similarities = finetuned_model.similarity(embeddings, embeddings)
print(embeddings.shape)
print(similarities)
```
## Model Type
- **Model type:** Sentence Transformer
- **Task:** Sentence similarity / semantic textual similarity
- **Language:** Arabic
- **Embedding size:** 768
- **Max sequence length:** 512
- **Similarity function:** Cosine similarity
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