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-47 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-comb-47 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-comb-47")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-comb-47") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-comb-47", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14f866206ddef7ec425b4945ed798d3215fe4c1e0a5a071d8fb18df50cfd18e0
- Size of remote file:
- 557 Bytes
- SHA256:
- f8f527a967fbb6c50b392e023e1a7794151e50c96afce5f162d65c995fb859f6
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