Instructions to use neeva/query2query with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use neeva/query2query with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("neeva/query2query") 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:
- aa6701343ad0e0a063101591ab3fa1d61ae1c01d8e5badedd59ef3cfe9aeefa0
- Size of remote file:
- 90.9 MB
- SHA256:
- bc46f932709bc706fc981d899e52e1ba5eed740108463283c03d0896f0dc4a77
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