Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use Gflorent/fossil_flex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Gflorent/fossil_flex with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Gflorent/fossil_flex") 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:
- 1d544b88117f2b9a26f619369b1c05b438e4d41459a1b9687ec83cc73a9d4e8e
- Size of remote file:
- 6.99 kB
- SHA256:
- 63916863cf1b0a9fdb81addf3fa39e2ceb65adcc13194576def684fa456b3e71
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