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:
- ac618b38f4ed7e3d1ddc0ef7a77a66eb7601f62966132599627f9400fb45e119
- Size of remote file:
- 1.23 GB
- SHA256:
- fe2dd052faab6cbef01de5c1181ae95548d3ac27ccb001215cc4fc090b3f62d0
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