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-693 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humor-Research/humor-detection-comb-693 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Humor-Research/humor-detection-comb-693", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Humor-Research/humor-detection-comb-693") model = AutoModelForSequenceClassification.from_pretrained("Humor-Research/humor-detection-comb-693", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb47bcd3cb71962c87c4334649ef6b8bde4c4c6d95452340ac808b49b9a5908d
- Size of remote file:
- 499 MB
- SHA256:
- daf68dd33d84ddc19048d4fcf35849ce990c4fedd043a33bd6b84812a5ad0ec9
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