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
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This model is a fine-tuned version of [DeBERTa](https://huggingface.co/microsoft/deberta-v3-base) on the [RaTE-NER]() dataset.
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# RaTE-NER-Deberta
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This model is a fine-tuned version of [DeBERTa](https://huggingface.co/microsoft/deberta-v3-base) on the [RaTE-NER]() dataset.
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