Sentence Similarity
sentence-transformers
Safetensors
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use rounit786757/e5-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rounit786757/e5-large-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rounit786757/e5-large-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:
- 84c62a6f6fe079c8431f9ea2c23e338ae7374262d08628910f63f1f1ac030388
- Size of remote file:
- 38.3 MB
- SHA256:
- 7a742948f822f10cffdec2cc67603990ed9f1ee9d61156d8acc5ab4812c4ab86
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