Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Watwat100/gpu2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Watwat100/gpu2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Watwat100/gpu2") 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:
- 895a85733a1f2b61b6e025f0d5bf4834fd2819fc1e76f7509c229f9fa4d81d1c
- Size of remote file:
- 438 MB
- SHA256:
- 9e8aeb4b39730d73795066879ddb50f5722e62e648960b0efedef9f14d602881
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