How to use LLMXperts/GATE-AraBert-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LLMXperts/GATE-AraBert-v1") sentences = [ "امرأة تكتب شيئاً", "مراهق يتحدث إلى فتاة عبر كاميرا الإنترنت", "امرأة تقطع البصل الأخضر.", "مجموعة من كبار السن يتظاهرون حول طاولة الطعام." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
How to use LLMXperts/GATE-AraBert-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LLMXperts/GATE-AraBert-v1") model = AutoModel.from_pretrained("LLMXperts/GATE-AraBert-v1")
This is GATE | General Arabic Text Embedding trained using SentenceTransformers in a multi-task setup. The system trains on the AllNLI and on the STS dataset.
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