Instructions to use thinkscientist/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thinkscientist/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thinkscientist/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thinkscientist/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("thinkscientist/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6e5f29ebf55401b931f11682d83b9dc84ea4802333f2edbea816b8bcbc1cbd6
- Size of remote file:
- 4.54 kB
- SHA256:
- 0d5d6e567a58b49cc0cf93b2cd14b4abd9157e4be85d2e48a62a8e1d61a1b906
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