Instructions to use airbusa388/supervised_test_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use airbusa388/supervised_test_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="airbusa388/supervised_test_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("airbusa388/supervised_test_1") model = AutoModelForSequenceClassification.from_pretrained("airbusa388/supervised_test_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10069a6e831ba68832138236147d9f3dec16ef0f2a7adbb70e1b0f8ed037c456
- Size of remote file:
- 268 MB
- SHA256:
- 84262a90b358bf751b089c4bf73b393e7f91125e3d594dfbc2f78529e170fdc0
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