Text Classification
Transformers
PyTorch
English
roberta
humor-detection
humor-classification
joke-detection
humor-vs-non-humor
binary-classification
english
nlp
computational-humor
Instructions to use Humor-Research/humor-detection-comb-23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-comb-23 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-comb-23")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-comb-23") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-comb-23") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5612fa6547dc96ac02a5eb01f7e2d80724a8afd37388d13bfc90f27b34bb9eb2
- Size of remote file:
- 499 MB
- SHA256:
- 661e060952f72a53954f2c3dc253b36e4d36e1172489b998b32ef19d261e4347
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