Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:244856
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/allstats-semantic-search-mini-model-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/allstats-semantic-search-mini-model-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/allstats-semantic-search-mini-model-v2") sentences = [ "Bulan apa inflasi sebesar 0,63 persen terjadi pada tahun 2013?", "Pada bulan Mei 2013 terjadi inflasi sebesar 0,2 persen", "Nilai Tukar Petani (NTP) April 2024 sebesar 116,79 atau turun 2,18 persen.", "Posisi Kredit Perbankan<sup>1</sup>dalam Rupiah dan Valuta Asing Menurut Sektor Ekonomi (miliar rupiah), 2016-2018" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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