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-one-liners-977 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-one-liners-977 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-one-liners-977")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-one-liners-977") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-one-liners-977", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c8fd3c25baa7a7e443462520139e63d3c7480ac2a608fd7f3bc1e866fec2014
- Size of remote file:
- 499 MB
- SHA256:
- 19e2483931460706382a0d83049082730cddc07e9d17868e4232e7f7a79ffd1d
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