Sentence Similarity
sentence-transformers
PyTorch
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use omarelsayeed/e5_base_tsdae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use omarelsayeed/e5_base_tsdae with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("omarelsayeed/e5_base_tsdae") 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:
- a56c752203b04168f27073c30dd1210a1154db3594a2f68a784a2ca451844fa6
- Size of remote file:
- 17.1 MB
- SHA256:
- e54a06c2a8b8041b979a9167588cf3adec464fb634ad3b32fbc412c8a4398303
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