Instructions to use simonschoe/TransformationTransformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonschoe/TransformationTransformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonschoe/TransformationTransformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonschoe/TransformationTransformer") model = AutoModelForSequenceClassification.from_pretrained("simonschoe/TransformationTransformer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b953bba77b989251f57f755b51aa800c2c82378c3de602d2abfc28838bf8c84
- Size of remote file:
- 499 MB
- SHA256:
- 192a06a46167a8660406d178d07f87b7dd15d057634bd2d58c4147c5fdda3f25
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