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:
- 54d04dfa3cdb68a964c4022defbdc7814575380264214b0efc1f1056fb87a563
- Size of remote file:
- 1.6 kB
- SHA256:
- 447fef4086003ae614a0dcc7937934670b50df5a927d38ee94157a0b89ca955a
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