Instructions to use figmtu/deberta-v3-aac-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use figmtu/deberta-v3-aac-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="figmtu/deberta-v3-aac-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("figmtu/deberta-v3-aac-classifier") model = AutoModelForSequenceClassification.from_pretrained("figmtu/deberta-v3-aac-classifier") - Notebooks
- Google Colab
- Kaggle
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language: en
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base_model: microsoft/deberta-v3-base
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license: cc-by-4.0
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This is a three-way classifier built on top of [DeBERTaV3](https://huggingface.co/microsoft/deberta-v3-base).
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language: en
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base_model: microsoft/deberta-v3-base
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license: cc-by-4.0
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library_name: transformers
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This is a three-way classifier built on top of [DeBERTaV3](https://huggingface.co/microsoft/deberta-v3-base).
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