Sentence Similarity
sentence-transformers
Safetensors
Indonesian
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:6198
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use Pustekhan-ITB/indoedubert-bge-m3-exp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Pustekhan-ITB/indoedubert-bge-m3-exp2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Pustekhan-ITB/indoedubert-bge-m3-exp2") sentences = [ "Seekor kucing hitam dan putih yang sedang bermain dengan keranjang wol.", "Dua ekor anjing berlari melintasi lapangan berumput.", "Seorang pria mengiris bawang.", "Seekor kucing hitam dan putih yang sedang berbaring di atas selimut." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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