Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:1432
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/allstats-search-large-bpstable-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/allstats-search-large-bpstable-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/allstats-search-large-bpstable-v1") sentences = [ "Input-output domestik Indonesia: 17 sektor usaha, harga produsen, data tahun 2016 (juta Rp)", "Impor Besi dan Baja Menurut Negara Asal Utama, 2017-2023 ", "IHK dan Rata-rata Upah per Bulan Buruh Hotel di Bawah Mandor (Supervisor), 1996-2014 (1996=100) ", "Tabel Input-Output Indonesia Transaksi Domestik Atas Dasar Harga Produsen (17 Lapangan Usaha), 2016 (Juta Rupiah) " ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c868f6ae026bc63d64f2f4d9ca9518eb5dbd9e9dba827b2d253a49694f1ab66f
- Size of remote file:
- 1.34 GB
- SHA256:
- 571d77e13317318c61517a3957be66da18e48e6355c79923b587f37727ca0fee
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