Text Classification
Transformers
PyTorch
English
ma2za/roberta-emotion
feature-extraction
Emotion Classification
custom_code
Eval Results (legacy)
Instructions to use ma2za/roberta-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ma2za/roberta-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ma2za/roberta-emotion", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ma2za/roberta-emotion", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:e3674dd953d9ec9fddbef55020613de62af46e6df80edd577a7eaa3f70222396
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size 498629536
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