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-unfun-me-693 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-unfun-me-693 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-unfun-me-693")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-unfun-me-693") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-unfun-me-693", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac918feedcb08e58c795c49890e2a60bee1b1c7468ab7c40f42170d5013c4bf1
- Size of remote file:
- 557 Bytes
- SHA256:
- 290e135cfeb5a5e5e0565365ff0b5e01beecf69fc5deef2d127b0fc88aa53483
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