Text Classification
Transformers
PyTorch
English
roberta
sentiment
emotion
twitter
reddit
text-embeddings-inference
Instructions to use j-hartmann/emotion-english-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use j-hartmann/emotion-english-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="j-hartmann/emotion-english-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("j-hartmann/emotion-english-roberta-large") model = AutoModelForSequenceClassification.from_pretrained("j-hartmann/emotion-english-roberta-large") - Inference
- Notebooks
- Google Colab
- Kaggle
Description βΉ
With this model, you can classify emotions in English text data. The model was trained on 6 diverse datasets and predicts Ekman's 6 basic emotions, plus a neutral class:
- anger π€¬
- disgust π€’
- fear π¨
- joy π
- neutral π
- sadness π
- surprise π²
The model is a fine-tuned checkpoint of RoBERTa-large.
For further details on this emotion model, please refer to the model card of its DistilRoBERTa version.
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