Instructions to use pqai/pqai-vectorizer-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pqai/pqai-vectorizer-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pqai/pqai-vectorizer-v3") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a535151282049b09f841abf25c4ab632233583044855468a4e86ec001c54fde1
- Size of remote file:
- 90.9 MB
- SHA256:
- 7df4dd845def1f96394dd86c8d59a4a0c89784249252e4d527ce1de2efa80a9c
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