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-977 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-comb-977 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-comb-977")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-comb-977") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-comb-977") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fcd2736d1fd8dab179c1d175271798f6394d80dec5b2ca31cf4f050ae42df23
- Size of remote file:
- 499 MB
- SHA256:
- 03a227d22cb747063aed5197909b7754baa6b3e2db664c15aa713f4624d03b8d
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