Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:80
loss:CoSENTLoss
text-embeddings-inference
Instructions to use ousaxkos/result_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ousaxkos/result_model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ousaxkos/result_model") sentences = [ "A woman wearing all white and eating, walks next to a man holding a briefcase.", "A married couple is sleeping.", "The people are eating omelettes.", "Two adults walk across a street." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 91 Bytes
f55a45b | 1 2 3 4 5 | {
"embedding_dimension": 1024,
"pooling_mode": "mean",
"include_prompt": true
} |