Instructions to use prinsINT/deberta-v3-base-uner-down200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prinsINT/deberta-v3-base-uner-down200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="prinsINT/deberta-v3-base-uner-down200")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("prinsINT/deberta-v3-base-uner-down200") model = AutoModelForTokenClassification.from_pretrained("prinsINT/deberta-v3-base-uner-down200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from prinsINT/deberta-v3-base-uner-down200: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
-
https://huggingface.co/prinsINT/deberta-v3-base-uner-down200/resolve/main/tokenizer.json
- Command line
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hf download hf://prinsINT/deberta-v3-base-uner-down200/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/prinsINT/deberta-v3-base-uner-down200/resolve/main/tokenizer.json
8.66 MB
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