Instructions to use abidlabs/test_push_output_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abidlabs/test_push_output_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abidlabs/test_push_output_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abidlabs/test_push_output_4") model = AutoModelForSequenceClassification.from_pretrained("abidlabs/test_push_output_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b60daa4d7c6c283a2c10f42c79e3a3dc30cf6edcd24180e77ad8fb2a745054cb
- Size of remote file:
- 5.14 kB
- SHA256:
- c9a1a935698795ddea3d4fd34ea6054be028cacb488a8bb492cc5b410c8bee56
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