Instructions to use bertugmirasyedi/deberta-v3-base-book-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertugmirasyedi/deberta-v3-base-book-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bertugmirasyedi/deberta-v3-base-book-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bertugmirasyedi/deberta-v3-base-book-classification") model = AutoModelForSequenceClassification.from_pretrained("bertugmirasyedi/deberta-v3-base-book-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 258e3c9376caa4bb10e565ffbddac55abb9f52e47a61336ec8b0040d50d85a10
- Size of remote file:
- 738 MB
- SHA256:
- 7a248297e262c863f69facde3427a9cfb422dd5dc6d9b32be53d42a70da8eda0
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