| cff-version: 1.2.0 |
| message: Please cite this project using these metadata. |
| title: "Gradio: Hassle-free sharing and testing of ML models in the wild" |
| abstract: >- |
| Accessibility is a major challenge of machine learning (ML). |
| Typical ML models are built by specialists and require |
| specialized hardware/software as well as ML experience to |
| validate. This makes it challenging for non-technical |
| collaborators and endpoint users (e.g. physicians) to easily |
| provide feedback on model development and to gain trust in |
| ML. The accessibility challenge also makes collaboration |
| more difficult and limits the ML researcher's exposure to |
| realistic data and scenarios that occur in the wild. To |
| improve accessibility and facilitate collaboration, we |
| developed an open-source Python package, Gradio, which |
| allows researchers to rapidly generate a visual interface |
| for their ML models. Gradio makes accessing any ML model as |
| easy as sharing a URL. Our development of Gradio is informed |
| by interviews with a number of machine learning researchers |
| who participate in interdisciplinary collaborations. Their |
| feedback identified that Gradio should support a variety of |
| interfaces and frameworks, allow for easy sharing of the |
| interface, allow for input manipulation and interactive |
| inference by the domain expert, as well as allow embedding |
| the interface in iPython notebooks. We developed these |
| features and carried out a case study to understand Gradio's |
| usefulness and usability in the setting of a machine |
| learning collaboration between a researcher and a |
| cardiologist. |
| authors: |
| - family-names: Abid |
| given-names: Abubakar |
| - family-names: Abdalla |
| given-names: Ali |
| - family-names: Abid |
| given-names: Ali |
| - family-names: Khan |
| given-names: Dawood |
| - family-names: Alfozan |
| given-names: Abdulrahman |
| - family-names: Zou |
| given-names: James |
| doi: 10.48550/arXiv.1906.02569 |
| date-released: 2019-06-06 |
| url: https: |
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