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| import gradio as gr | |
| title = "FlauBERT" | |
| description = "Gradio Demo for FlauBERT. 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/1912.05372' target='_blank'>FlauBERT: Unsupervised Language Model Pre-training for French</a></p>" | |
| examples = [ | |
| ["Paris est la <special1> de la France.","flaubert_small_cased"] | |
| ] | |
| io1 = gr.Interface.load("huggingface/flaubert/flaubert_small_cased") | |
| io2 = gr.Interface.load("huggingface/flaubert/flaubert_base_cased") | |
| def inference(inputtext, model): | |
| if model == "flaubert_small_cased": | |
| outlabel = io1(inputtext) | |
| else: | |
| outlabel = io2(inputtext) | |
| return outlabel | |
| gr.Interface( | |
| inference, | |
| [gr.inputs.Textbox(label="Context",lines=10),gr.inputs.Dropdown(choices=["flaubert_small_cased","flaubert_base_cased"], type="value", default="flaubert_small_cased", label="model")], | |
| [gr.outputs.Label(label="Output")], | |
| examples=examples, | |
| article=article, | |
| title=title, | |
| description=description).launch(enable_queue=True, cache_examples=True) |