Instructions to use snowdere/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snowdere/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="snowdere/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("snowdere/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("snowdere/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db768c78854d60c407399fc9f335354af769e62302679a80f7f047e61db2e033
- Size of remote file:
- 3.52 kB
- SHA256:
- fc23a1a30465bda2776cf03be920aa60f341aa05347bc7449c1afec35172bfd4
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