Instructions to use Azma-AI/deberta-base-multi-label-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Azma-AI/deberta-base-multi-label-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Azma-AI/deberta-base-multi-label-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Azma-AI/deberta-base-multi-label-classifier") model = AutoModelForSequenceClassification.from_pretrained("Azma-AI/deberta-base-multi-label-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d173b7e9dc9a368c35f3c2584bd64a1fa0d1b51856a880e8bdaa43d33d2bf44
- Size of remote file:
- 738 MB
- SHA256:
- d58b81ba665995176104a66f7b7d0b9e2e412564f6b33917e84c4eb920946841
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