Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:212930
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use yahyaabd/allstats-semantic-search-model-v1-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yahyaabd/allstats-semantic-search-model-v1-2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yahyaabd/allstats-semantic-search-model-v1-2") sentences = [ "analisis perekonomian indonesia triwulan i 2007", "Indikator Ekonomi Februari 2017", "Perkembangan Harga Produsen Gabah Maret 2021", "Hasil Survei Komoditas Perikanan Potensi 2021 Profil Rumah Tangga Usaha Budidaya Rumput Laut" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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