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:
- fd9e73d861699994da5b15ae46cc4149369bb407556988bd79be9fcae2e1e128
- Size of remote file:
- 997 MB
- SHA256:
- 1de3f209c17eafb69423889cf1d44215a80e68f586e148f45aea6bca0b77b650
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