| import gradio as gr | |
| from acrobert import acronym_linker | |
| def greet(sentence): | |
| results = acronym_linker(sentence, mode='acrobert') | |
| return results | |
| sample_list = [ | |
| "The LDA is an example of a topic model.", | |
| "Using a camera sensor, LDA judges the position of your vehicle in relation to the road markings below. This keeps the driver consistently aware of their situation, so that corrective action can be taken when needed.", | |
| "AI is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. ", | |
| "In the United States, the AI for potassium for adults is 4.7 grams", | |
| "This new genome assembly and the annotation are tagged as a RefSeq genome by NCBI and thus provide substantially enhanced genomic resources for future research involving S. scovelli.", | |
| "In this study, we found that miR-34a demonstrated greater expression in the lungs of patients with IPF and in mice with experimental pulmonary fibrosis , with its primary localization in lung fibroblasts.", | |
| ] | |
| iface = gr.Interface(fn=greet, inputs="text", outputs="text", examples=sample_list, cache_examples=False) | |
| iface.launch() |