Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use OneFly7/crossencoder_ep10_bs4_trans3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use OneFly7/crossencoder_ep10_bs4_trans3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("OneFly7/crossencoder_ep10_bs4_trans3") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bbf978d5e037d79a977ad8175cc9b33d788cb8c0f2feaabbf019fe466734874
- Size of remote file:
- 1.11 GB
- SHA256:
- 0019e812f712210525a201992672ee5b8c38e791c8cc26467b84a5c4e83d9be0
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