Instructions to use JoBeer/sentence-t5-base-eclass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use JoBeer/sentence-t5-base-eclass with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("JoBeer/sentence-t5-base-eclass") 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:
- d19ebe82ced8fd88021038dcfc48109c899a698c2dca2026a1c0d48d5f455365
- Size of remote file:
- 2.36 MB
- SHA256:
- 714c25ae57cd7c5b47efb78f53ef93a5fd2a170aa922e41c5200296f2e0c42be
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