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:
- 1a15d39118f3569b5216e90e93d502f431f82afe9a8cc5846dc7f616d1addebf
- Size of remote file:
- 129 MB
- SHA256:
- 865097bc1b1d5792f842bd245048d774360bd61bcc11530bd53c21af62fc300d
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