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:
- f2ce4b189e8f6bb0438741c6209102aafddb1c7917678583a1bb6288e8e903d9
- Size of remote file:
- 7.12 kB
- SHA256:
- 3540a9beda14a3bc165743b2b4c769efaf7ecb2c39ad09e5e299eee87482a983
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