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-693 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-comb-693 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-comb-693")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-comb-693") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-comb-693") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5a2625cd489787c279e2997a96af949c1396ddbc3a1e45454b8068c87a7d3c2
- Size of remote file:
- 997 MB
- SHA256:
- 125270372ae2d027557b459f60047f0a5aa1ad731c4161b52acb7d7a37f94010
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