Instructions to use lambdaofgod/document_nbow_embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lambdaofgod/document_nbow_embedder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lambdaofgod/document_nbow_embedder") 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:
- 4b1ef213946cf436adf4916cde56a150f57120e1b7a0f41d7b10351c57889a54
- Size of remote file:
- 67.2 MB
- SHA256:
- 46cb112d8f96d43f883e446f9cac2b5dfc39dff7831d020919e10fd439ad1ce2
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