Instructions to use XRandomForest/mymodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use XRandomForest/mymodel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("XRandomForest/mymodel") 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:
- cb10bcd1ab32ec6ad9efe67c7525ea31f609f09ea6b46dc495e445c7dfa150ca
- Size of remote file:
- 438 MB
- SHA256:
- 114502c95f9c553e1dd6627a5ff5db3238619bb51047e77ab19871192427418d
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