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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4683d083439dbecc289b627d38f8c90d6d04ba8ce82193c98a217715af8f30db
- Size of remote file:
- 3.58 kB
- SHA256:
- 029d10122f479d9abcfafee6fc4e9cfc495d0ceeef61ca9231b326ec13bdc7f4
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