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| import gradio as gr | |
| title = "BART" | |
| description = "Gradio Demo for BART, 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/1910.13461' target='_blank'>BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension</a></p>" | |
| examples = [ | |
| ["I have a problem with my iphone that needs to be resolved asap!!","bart-large-mnli","urgent, not urgent, phone, tablet, computer",False] | |
| ] | |
| io1 = gr.Interface.load("huggingface/facebook/bart-large-mnli") | |
| io2 = gr.Interface.load("huggingface/facebook/bart-large-cnn") | |
| def inference(text, model,class_names,allow_multiple): | |
| if model == "bart-large-mnli": | |
| outlabel = io1(text,class_names,allow_multiple) | |
| outtext = "" | |
| else: | |
| outtext = io2(text) | |
| outlabel = {} | |
| return outlabel, outtext | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Input",lines=10),gr.inputs.Dropdown(choices=["bart-large-mnli","bart-large-cnn"], type="value", default="bart-large-mnli", label="model"),gr.inputs.Textbox(label="Possible class names (comma-separated)"),gr.inputs.Checkbox(default=False, label="Allow multiple true classes")], | |
| ["label","textbox"], | |
| examples=examples, | |
| article=article, | |
| title=title, | |
| description=description).launch(enable_queue=True, cache_examples=True) | |