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:
- b7c3bf1d2c7cc6ac1ee3a94779998972916cc7231823261110924c6f48a3de7c
- Size of remote file:
- 3.58 kB
- SHA256:
- 492101fc6f48c74a372fc4dafcc83bbbfe07a518b904e7bf3095e6be8adcc1f3
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