Sentence Similarity
sentence-transformers
PyTorch
mpnet
feature-extraction
text-embeddings-inference
Instructions to use florentgbelidji/setfit_emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use florentgbelidji/setfit_emotion with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("florentgbelidji/setfit_emotion") 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:
- d030cad05ad302b68bf135b08e62723ba3a2ec30d879c3b654533f85004f31ef
- Size of remote file:
- 438 MB
- SHA256:
- 7d687e7e893e4806831ada4eb53063e3a901e92a774fdc3ab4e47e6d2a72a340
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