Text Classification
sentence-transformers
Safetensors
English
Chinese
xlm-roberta
mteb
text-embeddings-inference
Eval Results (legacy)
Instructions to use HJUNN/bge_margin_cross_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HJUNN/bge_margin_cross_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HJUNN/bge_margin_cross_encoder") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3c720da8c35ff3b363e2bbb6e76f9ee80b959f210ab41139212804f2f3385c8
- Size of remote file:
- 17.1 MB
- SHA256:
- 7f5813aea5b2b5d64ae358afca15f61e3800df4c257bbc24401485426a61fb82
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.