Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:8884
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use PrabalAryal/Sentence_Transformer_v0.0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PrabalAryal/Sentence_Transformer_v0.0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PrabalAryal/Sentence_Transformer_v0.0.1") sentences = [ "De deur tussen twee kamers", "Verschillende buren hebben hetzelfde probleem", "Alle lampen in de gemeenschappelijke ruimtes", "De scheidingsdeur" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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