Instructions to use Kate-lf/emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kate-lf/emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kate-lf/emotion-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kate-lf/emotion-classification") model = AutoModelForSequenceClassification.from_pretrained("Kate-lf/emotion-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 326f4c828a3063b9299174fe10505296c7d8bcd5ec23eb99ff320b06084bf5ad
- Size of remote file:
- 5.84 kB
- SHA256:
- 7cd447230fa5f24fd4d317f21bcfe73c78e26b813d1cd99d1fc1576829aa2524
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