Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:11002
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use bwang0911/word-order-bge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bwang0911/word-order-bge with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bwang0911/word-order-bge") sentences = [ "Man jumps alone on a desert road with mountains in the background.", "A man jumps on the desert road", "A man plays a silver electric guitar.", "A man doesnt jump on the desert road" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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