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| import gradio as gr | |
| title = "T5" | |
| description = "Gradio Demo for T5. To use it, simply add your text, or click one of the examples to load them. Read more at the links below." | |
| article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1910.10683' target='_blank'>Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer</a></p>" | |
| examples = [ | |
| ['My name is Sarah and I live in London',"t5-base"] | |
| ] | |
| io1 = gr.Interface.load("huggingface/t5-base") | |
| io2 = gr.Interface.load("huggingface/t5-small") | |
| io3 = gr.Interface.load("huggingface/t5-large") | |
| io4 = gr.Interface.load("huggingface/t5-3b") | |
| def inference(text, model): | |
| if model == "t5-base": | |
| outtext = io1(text) | |
| elif model == "t5-small": | |
| outtext = io2(text) | |
| elif model == "t5-large": | |
| outtext = io3(text) | |
| else: | |
| outtext = io4(text) | |
| return outtext | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["t5-base","t5-small","t5-large","t5-3b"], type="value", default="t5-base", label="model") | |
| ], | |
| gr.outputs.Textbox(label="Output"), | |
| examples=examples, | |
| article=article, | |
| title=title, | |
| description=description).launch(enable_queue=True) |