Instructions to use ctoraman/deprem-berturk-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctoraman/deprem-berturk-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ctoraman/deprem-berturk-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ctoraman/deprem-berturk-binary") model = AutoModelForSequenceClassification.from_pretrained("ctoraman/deprem-berturk-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ef64eca3a9418b675792f2a5e00e692cb303033a85afd59491e88725b4170f9
- Size of remote file:
- 443 MB
- SHA256:
- 80ded6fd0dfd331c11bc4f70a142d806a9e469a09cd5a94b130c912dd5167efe
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