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:
- dc8f92f07278effbf9c45dc5118ff9c8ae95eb06dddd239cadd05d4bcd39efd6
- Size of remote file:
- 438 MB
- SHA256:
- 27281b2e1eb1ef9ed7a82e87d1e0cc87b248524684f2cdedc37d27ad1f628b1c
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