Instructions to use Gunulhona/tbecmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gunulhona/tbecmodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Gunulhona/tbecmodel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Gunulhona/tbecmodel") model = AutoModelForSequenceClassification.from_pretrained("Gunulhona/tbecmodel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35db5603c0d1641447e8e7a8b0fc7274dea8f79cae30cb37193370cae04a3cd4
- Size of remote file:
- 498 MB
- SHA256:
- 7a11f2f927a5b324726ebe3b916c5bd7f5d1d0bbe71bb77b042927bb5bf808fa
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