Instructions to use Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2") model = AutoModelForTokenClassification.from_pretrained("Isotonic/mdeberta-v3-base_finetuned_ai4privacy_v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c61161d9abb487b8da0d3016bc35290c25462e3abadb59573aed3af46d04a22
- Size of remote file:
- 4.66 kB
- SHA256:
- 48b353cb8f05f3d66880dab06ade38b03889588b602ee17fd65f600907adf018
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