Instructions to use razzaghi/tuning_intfloat_E5_small_encode_3m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use razzaghi/tuning_intfloat_E5_small_encode_3m with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("razzaghi/tuning_intfloat_E5_small_encode_3m") 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:
- b5fee8c131cd413addfa52ee98f0300f56fd1408a32bf36e7174a2fea4661178
- Size of remote file:
- 471 MB
- SHA256:
- 77841d67cbced5dc0e83111c39f305b9b0968f101cd468cd447ce166d9de1cb0
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