Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:23478
loss:ContrastiveLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/allstats-semantic-base-v1-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/allstats-semantic-base-v1-3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/allstats-semantic-base-v1-3") sentences = [ "Pekerja anak Indonesia: Buku panduan 2022 (pr & pasca pandemi)", "Statistik Perusahaan Hak Pengusahaan Hutan 2010", "Statistik Kriminal 2016", " Buletin Statistik Perdagangan Luar Negeri Ekspor Menurut Kelompok Komoditi dan Negara, November 2020" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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