Instructions to use XRandomForest/mymodel2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use XRandomForest/mymodel2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("XRandomForest/mymodel2") 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:
- 071e325a1c6e738ab07bc2b57406e0704b083e8800073fbeb93df883faaea62f
- Size of remote file:
- 19.3 kB
- SHA256:
- c3365e1faadfaa2879e50d6326cc0cd72de60843f0ca84cffd9a3544a02a8dab
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