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:
- 58dce923cccc4006fb79786f9491512762b2f26eefcfc5a6d34e19b54f97755d
- Size of remote file:
- 4.03 kB
- SHA256:
- b3ddde43c74acbdc9a7d7f40677094d2857b44dd26e651fda755950ea0a80dae
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