Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:350
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/tes_upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/tes_upload with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/tes_upload") sentences = [ "Data pengeluaran bulanan rumah tangga pedesaan untuk konsumsi makanan dan non-makanan per provinsi, tahun berapa saja tersedia?", "Sistem Neraca Sosial Ekonomi Indonesia Tahun 2022 (84 x 84)", "Persentase RataRata Pengeluaran per Kapita Sebulan Untuk Makanan dan Bukan Makanan di Daerah Perdesaan Menurut Provinsi, 2007-2024", "Nilai Impor Jawa Madura Menurut Pelabuhan Impor di Pulau Jawa Madura Tahun 2009 - 2013 (Juta US $) 1)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
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