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
- Xet hash:
- 3d72d21bb0fc91a93009520cf42278cf4a004db54fd67e2bd40c4d2cd1e54ab1
- Size of remote file:
- 2.24 GB
- SHA256:
- c79ed02fffd54520736eb1e2ae44fa2c569e1427220ccec360c690151461f91a
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