Instructions to use andersborges/model2vecdk-stem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use andersborges/model2vecdk-stem with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("andersborges/model2vecdk-stem") - sentence-transformers
How to use andersborges/model2vecdk-stem with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("andersborges/model2vecdk-stem") 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:
- e7572454fa628603370fe2212a903583cfc25402fc82a096b4e55853580d9cd7
- Size of remote file:
- 194 MB
- SHA256:
- e994bef428c2e9e2ce0d46bcd964536636bea9848654297e361d149e28a0067a
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