Instructions to use okovtun/bert-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use okovtun/bert-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="okovtun/bert-emotion")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("okovtun/bert-emotion") model = AutoModelForSequenceClassification.from_pretrained("okovtun/bert-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a196d6451b8a523dc7fe0659632fe7376feeb736db8a1f1acec746a1f035e35
- Size of remote file:
- 3.18 kB
- SHA256:
- d9b7f391ec821607e9d979cad2b8494e7ac6377909cf45c557c6945278af1c6f
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