Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use CDXV/Sentence-Similarity-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use CDXV/Sentence-Similarity-Models with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CDXV/Sentence-Similarity-Models") sentences = [ "Children smiling and waving at camera", "The kids are frowning", "The people are eating omelettes.", "Near a couple of restaurants, two people walk across the street." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 143 Bytes
5c6e055 | 1 2 3 4 | epoch,steps,cosine_pearson,cosine_spearman
1.0,10,0.037203406650844886,0.07040057435528181
1.0,10,-0.22939457943411037,-0.18637822325921868
|