Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use copenlu/spiced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use copenlu/spiced with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("copenlu/spiced") 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:
- ff76eb5adc8e981db7dbe58434ea9225f6826e07761205c9a647c812e5ff0f06
- Size of remote file:
- 438 MB
- SHA256:
- 278771ac10f3d2e77faa86b065dc9183795fc7e9fafddf6f50b4d9d1dfaf59be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.