README.md

---
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