Instructions to use krumeto/text-class-tutorial-model2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use krumeto/text-class-tutorial-model2vec with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("krumeto/text-class-tutorial-model2vec") - sentence-transformers
How to use krumeto/text-class-tutorial-model2vec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("krumeto/text-class-tutorial-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:
- 9c4160283ceefd3f8bf607b1f84430b0458e5e41c41d179c2277c6df937b23e9
- Size of remote file:
- 129 MB
- SHA256:
- 9354a7d6f65894001842b61c87bf1e643032c249fdb7f11d4173ac8be93394f2
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