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:
- 3dcbcd8b589e74759111cb88954bf03a7d33bdf5214044e325b3c0da22528de4
- Size of remote file:
- 69 Bytes
- SHA256:
- 8a30b1330f70b9cbd264085c41abbf6e6622654a5afd27c2cb5f91b8140d63e0
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