Instructions to use facetnet/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use facetnet/test-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("facetnet/test-model") 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:
- 09ebda0292d2f717142b60970aedbd8dcdc0615a3b17004880a5965d0ad7b311
- Size of remote file:
- 134 MB
- SHA256:
- f5c2bde2fe42cd2bf34c6665ba5a45b2562d277a95448489edc1af63c5b8b9db
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