Instructions to use mjaydenkim/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjaydenkim/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mjaydenkim/test_trainer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjaydenkim/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("mjaydenkim/test_trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 498930415f9946a0f2975b7e097e726b15c6fa0b12f4cff75925525c30234fd6
- Size of remote file:
- 3.96 kB
- SHA256:
- 2d09e699e77c2354244a8f3d4f4ae8083934893de227551b2f6e939d4317cba1
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