Sentence Similarity
sentence-transformers
Safetensors
deberta-v2
feature-extraction
Generated from Trainer
dataset_size:40338
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use richie-ghost/sbert_ft_cross-encoder-nli-deberta-v3-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use richie-ghost/sbert_ft_cross-encoder-nli-deberta-v3-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("richie-ghost/sbert_ft_cross-encoder-nli-deberta-v3-large") sentences = [ "\"Rumpelstilsken, I command the sun to set!\" He seemed to sense a hesitation in his mind, and then the impression of jeweled gears turning.", "A football game is playing.", "He sensed hesitation when commanding Rumpelstiltskin.", "I ran and he saw me immediately." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K