Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use quarkss/indobert-base-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use quarkss/indobert-base-stsb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("quarkss/indobert-base-stsb") sentences = [ "Dua ekor anjing berenang di kolam renang.", "Anjing-anjing sedang berenang di kolam renang.", "Seekor binatang sedang berjalan di atas tanah.", "Seorang pria sedang menyeka pinggiran mangkuk." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K