Instructions to use ppsingh/roberta-finetuned-qa-policy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppsingh/roberta-finetuned-qa-policy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ppsingh/roberta-finetuned-qa-policy")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ppsingh/roberta-finetuned-qa-policy") model = AutoModelForQuestionAnswering.from_pretrained("ppsingh/roberta-finetuned-qa-policy") - Notebooks
- Google Colab
- Kaggle
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README.md
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# roberta-finetuned-qa-policy
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This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the
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## Model description
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## Training and evaluation data
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https://huggingface.co/datasets/GIZ/policy_qa_v0
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## Training procedure
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# roberta-finetuned-qa-policy
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This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the [Policy_QA](https://huggingface.co/datasets/GIZ/policy_qa_v0) dataset.
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## Model description
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## Training and evaluation data
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[Policy QA](https://huggingface.co/datasets/GIZ/policy_qa_v0)
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## Training procedure
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