Instructions to use ctoraman/deprem-mdeberta-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctoraman/deprem-mdeberta-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ctoraman/deprem-mdeberta-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ctoraman/deprem-mdeberta-binary") model = AutoModelForSequenceClassification.from_pretrained("ctoraman/deprem-mdeberta-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62829fb8782e4b5301714a448d4a5f6c7615fadf7540a4b63e9fc8faf8423271
- Size of remote file:
- 2.67 kB
- SHA256:
- cb4be0d06f3948d4d34b5babf8505042384e3f758a07df0593677b2fcc4f8075
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