Sentence Similarity
sentence-transformers
Safetensors
English
roberta
feature-extraction
loss:AdaptiveLayerLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use tomaarsen/distilroberta-base-nli-adaptive-layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/distilroberta-base-nli-adaptive-layer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/distilroberta-base-nli-adaptive-layer") sentences = [ "Certainly.", "'Of course.'", "The idea is a good one.", "the woman is asleep at home" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K