Feature Extraction
sentence-transformers
Safetensors
Serbian
roberta
sentence-similarity
emotion-detection
serbian
text-embeddings-inference
Instructions to use procesaur/Emo355 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use procesaur/Emo355 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("procesaur/Emo355") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Upload labels_emo.json
Browse files- labels_emo.json +1 -0
labels_emo.json
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{"trust": 0, "anger": 1, "sadness": 2, "surprise": 3, "fear": 4, "disgust": 5, "joy": 6, "anticipation": 7}
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