Instructions to use htet-98/sea-lion-humor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use htet-98/sea-lion-humor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="htet-98/sea-lion-humor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("htet-98/sea-lion-humor") model = AutoModelForSequenceClassification.from_pretrained("htet-98/sea-lion-humor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 376421d1b30cd6fef44f934b0b33f708cae9e1600af70b567f42bd2c6c2b34ad
- Size of remote file:
- 33.4 MB
- SHA256:
- c174d4fb9fab2c207b31ecc6b4b9de7dd9eddda12434f7397911981cd63e8aac
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