Instructions to use fmurray/emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmurray/emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fmurray/emotions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fmurray/emotions") model = AutoModelForSequenceClassification.from_pretrained("fmurray/emotions", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0027217cc9284678d493ffc359e3d30c073340f2ef01f72f5cd62a9ebce5ce9
- Size of remote file:
- 268 MB
- SHA256:
- a7312dce1fc873618f3be28e157065a871dc3f9f2977087786acb697280e2027
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