Instructions to use lambdaofgod/paperswithcode_word2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lambdaofgod/paperswithcode_word2vec with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lambdaofgod/paperswithcode_word2vec") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8dbcaab12bd4e20da55571abc164a7b34242ab2570f9d418679c08efcbb69ac0
- Size of remote file:
- 118 MB
- SHA256:
- 2f0028a20b8d6ab7c6c73d50d7edb19a88eedb9e5a3f3fb0b489780f4a695efa
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