Instructions to use dima806/sarcasm-detection-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/sarcasm-detection-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/sarcasm-detection-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/sarcasm-detection-distilbert") model = AutoModelForSequenceClassification.from_pretrained("dima806/sarcasm-detection-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5516c41968363606a50720b82dadb45bc96bb6e710b28e0a83d641831289d2b
- Size of remote file:
- 438 MB
- SHA256:
- 7b3709ac360fba07e443921e1a294e4c72bc1f8cc988ecbc757d0685836e89cc
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