Sentence Similarity
sentence-transformers
Safetensors
Transformers.js
Transformers
Arabic
bert
feature-extraction
dataset_size:75000
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
mteb
text-embeddings-inference
Instructions to use LLMXperts/Arabic-Triplet-Matryoshka-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LLMXperts/Arabic-Triplet-Matryoshka-V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LLMXperts/Arabic-Triplet-Matryoshka-V2") 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] - Transformers.js
How to use LLMXperts/Arabic-Triplet-Matryoshka-V2 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('sentence-similarity', 'LLMXperts/Arabic-Triplet-Matryoshka-V2'); - Transformers
How to use LLMXperts/Arabic-Triplet-Matryoshka-V2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LLMXperts/Arabic-Triplet-Matryoshka-V2") model = AutoModel.from_pretrained("LLMXperts/Arabic-Triplet-Matryoshka-V2") - Notebooks
- Google Colab
- Kaggle
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