Instructions to use felixbrock/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use felixbrock/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="felixbrock/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("felixbrock/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("felixbrock/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cb87cf0d0959d59901a1a105a215723870d032ea3b2f74079cc41158b5cc2a5
- Size of remote file:
- 4.6 kB
- SHA256:
- 58450180a597fa43f034c05ce62ec0f329ba549396d714ed20f9746467bdd811
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