Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Watwat100/smol8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Watwat100/smol8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Watwat100/smol8") 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:
- acdf6b846b320fa719dd02aa40a9c12dcd98223c47e084658024911fab21d58a
- Size of remote file:
- 438 MB
- SHA256:
- 17424cf2926e588b35b92e0bab924638931e56b28eef4a7b225b3fc5e69d58d7
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