Instructions to use Gunulhona/tbbcmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gunulhona/tbbcmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gunulhona/tbbcmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gunulhona/tbbcmodel") model = AutoModelForSequenceClassification.from_pretrained("Gunulhona/tbbcmodel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c9b8c4b148c0d2d93373cb2b0491a9e5bd8ac1da9a2edc0d9957d373bf3a6823
- Size of remote file:
- 498 MB
- SHA256:
- a545f36a72daae4475e1cb826e39542bc5c1c369abd91869d7c90d1635cb462e
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