Instructions to use tmnam20/test-model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tmnam20/test-model1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tmnam20/test-model1") 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:
- 7c123ad154d1ed765df30a804734be7e3eb8415efcc210fc3b72f46d9e6438e2
- Size of remote file:
- 1.6 kB
- SHA256:
- 49598f000e4c9384fdc3f5202380ac7d5d9fdfc71a64f5702607688ee69ce9eb
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