Instructions to use BramVanroy/deberta-v3-base-uner-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BramVanroy/deberta-v3-base-uner-full with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BramVanroy/deberta-v3-base-uner-full")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("BramVanroy/deberta-v3-base-uner-full") model = AutoModelForTokenClassification.from_pretrained("BramVanroy/deberta-v3-base-uner-full") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76258776b9dc198bd469ed32c1544c4fc2375baf8ebf04820c664e3010f32cf8
- Size of remote file:
- 5.84 kB
- SHA256:
- 82bfacb16eb153a3614133f8af4569118f10f3d1a905c179d3a67c8eac38e7f1
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