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:
- b37509f9ea036cc54d3f1b63f65d6ef264440c7e8fdc691c5fff88d8c4c5691d
- Size of remote file:
- 3.58 kB
- SHA256:
- 64f15fab0ebcad6cc6b9a3d4e52b9e592cb46e7153068c3ae342bfb1a12de17c
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