Instructions to use Michael54546/ToxicTweet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Michael54546/ToxicTweet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Michael54546/ToxicTweet")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Michael54546/ToxicTweet") model = AutoModelForSequenceClassification.from_pretrained("Michael54546/ToxicTweet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d0635d20cd8e3d6163ca54085ba0ae7fdf272f1b2ca9ca43e1c4ad48571466d
- Size of remote file:
- 3.64 kB
- SHA256:
- 266db163e7e017a944e4c2a11d4bc20662199ad37ee6159286770ae6cc0675af
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