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:
- 5960324db3c4bf10d3e796e3130ea83c3386604bfe40970258c7bd0aa5d24b67
- Size of remote file:
- 3.58 kB
- SHA256:
- ec644cfbce667d08181f99ee33413d766261db151684b2decbe11352dce52b26
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