Instructions to use bertugmirasyedi/deberta-v3-base-level-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertugmirasyedi/deberta-v3-base-level-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bertugmirasyedi/deberta-v3-base-level-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bertugmirasyedi/deberta-v3-base-level-classification") model = AutoModelForSequenceClassification.from_pretrained("bertugmirasyedi/deberta-v3-base-level-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3ac60d6a6d1c60ba40ff5814fc62481edef2ac2161157359e17301705730ebd
- Size of remote file:
- 738 MB
- SHA256:
- 58a03fc2e1127bdd1ddb18888b306b3e91463db548fd81cf7ccba0fc38b26939
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