Instructions to use lewispons/email-classifiers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lewispons/email-classifiers with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lewispons/email-classifiers") 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:
- 3450f4b880e3d7899846b91504e4115c4abe3f4ac05819e94f0afc1443122629
- Size of remote file:
- 90.9 MB
- SHA256:
- 3b7968e5dec6f6dbc7c4099be22ac453d433d8c623b4f3435ad361e7115f8f53
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