Instructions to use DhanasriArul/Model2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use DhanasriArul/Model2vec with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("DhanasriArul/Model2vec") - sentence-transformers
How to use DhanasriArul/Model2vec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DhanasriArul/Model2vec") 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:
- 4c3587f03c90386f5c109436735436a62788da4696285b74c1bcab09d64d103f
- Size of remote file:
- 18.3 MB
- SHA256:
- 51c292478d94ec3a01461bdfa82eb0885d262eb09e615679b2d69dedb6ad09e7
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