Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
text-embeddings-inference
Instructions to use guyhadad01/cross_bin_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use guyhadad01/cross_bin_v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("guyhadad01/cross_bin_v2") 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:
- e6741ee3511f179030bd5bd94047af41a0557149618a695de8175e2230adf84b
- Size of remote file:
- 17.1 MB
- SHA256:
- 222975faa02f5257c6e8c734e85973e48c8d42d7d37d90b894c73efa1841d76a
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