Instructions to use macapa/emotion-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macapa/emotion-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="macapa/emotion-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("macapa/emotion-classifier") model = AutoModelForSequenceClassification.from_pretrained("macapa/emotion-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 934d66bcc25dfda92fe2813b1e47db922b5b1bc8b1969ab074edafda6c71d5a3
- Size of remote file:
- 5.24 kB
- SHA256:
- 0d0d759ca59350ff9e3b4534b72a3e18049a8b123507ef7737b9738be1553fd3
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