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narrativeqa-onnx
UKP-SQuARE/narrativeqa-onnx
narrativeqa-onnx is a machine learning model from UKP-SQuARE. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for adapter-transformers.
Access
Public
Updated Jan 15, 2023
Repo size
1.8 GB
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Repo makeup
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.onnx896 MB · 100%
At a glance
- Library
- adapter-transformers
- Model type
- bart
- Access
- Public
- Created
- Jan 15, 2023
- Updated
- Jan 15, 2023
- SHA
- bf41d687
Datasets
Model card
From the Hugging Face model README
ONNX export of Adapter hSterz/narrativeqa for facebook/bart-base
Conversion of AdapterHub/narrativeqa for UKP SQuARE
Usage
onnx_path = hf_hub_download(repo_id='UKP-SQuARE/narrativeqa-onnx', filename='model.onnx') # or model_quant.onnx for quantization
onnx_model = InferenceSession(onnx_path, providers=['CPUExecutionProvider'])
context = 'ONNX is an open format to represent models. The benefits of using ONNX include interoperability of frameworks and hardware optimization.'
question = 'What are advantages of ONNX?'
tokenizer = AutoTokenizer.from_pretrained('UKP-SQuARE/narrativeqa-onnx')
inputs = tokenizer(question, context, padding=True, truncation=True, return_tensors='np')
outputs = onnx_model.run(input_feed=dict(inputs), output_names=None)
Architecture & Training
<!-- Add some description here -->Evaluation results
<!-- Add some description here -->Citation
<!-- Add some description here -->- Library
- adapter-transformers
- Type
- bart
- Created
- Jan 15, 2023
- Updated
- Jan 15, 2023