Instructions to use rach405/test_trainer5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rach405/test_trainer5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rach405/test_trainer5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rach405/test_trainer5") model = AutoModelForSequenceClassification.from_pretrained("rach405/test_trainer5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d024379da478eb4f8cce0b15752850923d6186a081c10ee0c625993fabd1b13a
- Size of remote file:
- 2.99 kB
- SHA256:
- 2b928dcab489802c00b5e775adc164fcf86075520410fcb7e5194418b77561a1
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