Instructions to use SeppeV/JokeTailorTestModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeppeV/JokeTailorTestModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SeppeV/JokeTailorTestModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SeppeV/JokeTailorTestModel") model = AutoModelForSequenceClassification.from_pretrained("SeppeV/JokeTailorTestModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11a77add0f4416935d7b009c6d280e5bb96d7c9de0925ad3f65a4064eace7bcf
- Size of remote file:
- 5.43 kB
- SHA256:
- df346f175a080b989e92ad4a0ac409fa89218f480ca83e488ea5db68b5c83e81
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