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:
- 50b4255ed8efb1dca2a3e47b74c197a1dc59b48bda8877609f7a9a1dc69007f3
- Size of remote file:
- 439 MB
- SHA256:
- a87b4e9ca4a298282611c03d4a921c4f1d3cbb17d106904c3b7e15fab1ce0483
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