Sentence Similarity
Transformers
PyTorch
ONNX
sentence-transformers
Arabic
bert
feature-extraction
miniDense
passage-retrieval
knowledge-distillation
middle-training
text-embeddings-inference
Instructions to use prithivida/miniDense_arabic_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivida/miniDense_arabic_v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("prithivida/miniDense_arabic_v1") model = AutoModel.from_pretrained("prithivida/miniDense_arabic_v1") - sentence-transformers
How to use prithivida/miniDense_arabic_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("prithivida/miniDense_arabic_v1") sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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