Instructions to use stevemobs/deberta-base-finetuned-aqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevemobs/deberta-base-finetuned-aqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="stevemobs/deberta-base-finetuned-aqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stevemobs/deberta-base-finetuned-aqa") model = AutoModelForQuestionAnswering.from_pretrained("stevemobs/deberta-base-finetuned-aqa") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Update Hugging Face dataset ID
#2
by librarian-bot - opened
README.md
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@@ -3,7 +3,7 @@ license: mit
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tags:
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- generated_from_trainer
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datasets:
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- adversarial_qa
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model-index:
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- name: deberta-base-finetuned-aqa
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results: []
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tags:
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- generated_from_trainer
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datasets:
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- UCLNLP/adversarial_qa
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model-index:
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- name: deberta-base-finetuned-aqa
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results: []
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