Text Classification
Transformers
PyTorch
Safetensors
English
roberta
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use SamLowe/roberta-base-go_emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamLowe/roberta-base-go_emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamLowe/roberta-base-go_emotions") model = AutoModelForSequenceClassification.from_pretrained("SamLowe/roberta-base-go_emotions") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ae717fead9ed5c2796af924217a36a912899af564d840c8c1f9e5b1864dd0a6
- Size of remote file:
- 499 MB
- SHA256:
- 84d6d338b4cf63f0ed3c990a0ce748d32d1d2965c072f4645accaa71af3888c0
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