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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc8e75f49f009e5c288174d4c1bd9dc1c12a373363cf0c8bbfcf46a3b87b3ae6
- Size of remote file:
- 14.6 kB
- SHA256:
- 9c7d3576a2a0c6c53ae82d76a1d9eaacbdb9f7c1fa8c011f958033c6947df1b2
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