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-23 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-23 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-23")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-unfun-me-23") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-unfun-me-23", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Humor-Research/humor-detection-unfun-me-23: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Humor-Research/humor-detection-unfun-me-23/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Humor-Research/humor-detection-unfun-me-23/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Humor-Research/humor-detection-unfun-me-23/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- a6de559731ad410f7af8919c714767ba3cb5ce6d0d614e16abc3097d51315afc
- Size of remote file:
- 499 MB
- SHA256:
- b46294dcc5495ef624833ebf4fc7e19776b2e4f326e8be84e8a6c180b91f4604
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