Instructions to use W4nkel/electraTrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use W4nkel/electraTrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="W4nkel/electraTrain")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("W4nkel/electraTrain") model = AutoModelForSequenceClassification.from_pretrained("W4nkel/electraTrain") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ad546fb5ab521c886f61ff78e04d8ca0d44c02cdf3e7cc2a14e1d1deadb9713
- Size of remote file:
- 443 MB
- SHA256:
- 3a5cb18aa915bf10dd9537de7af9ae6f054e2d8762231a5427a44c5ca63523fe
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