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