Sentence Similarity
sentence-transformers
Safetensors
Minangkabau
Indonesian
English
eurobert
feature-extraction
text-embeddings
retrieval
minangkabau
minang
indonesian
nusax
low-resource
custom_code
Instructions to use apsys/minang-embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use apsys/minang-embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("apsys/minang-embedder", trust_remote_code=True) sentences = [ "Paliang suko bana makan siang di siko ayam jo ladonyo lamak bana harago lua biaso himat.", "I love having lunch here because the chicken and sambal are delicious and inexpensive.", "Kurang pas kalau bakunjuang ka banduang tanpa mancicipi batagor.", "The train ticket was booked yesterday." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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