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| import gradio as gr | |
| from transformers import pipeline | |
| model = pipeline(model="marksverdhei/t5-base-define") | |
| model.model.config.max_length = 300 | |
| description = """ | |
| Enter a word and a sentence that uses the word. We then generate a definition | |
| """ | |
| def predict(word, example) -> str: | |
| input_text = f"define \"{word}\": {example}" | |
| output = model(input_text, truncation=True) | |
| output_text = output[0]["generated_text"] | |
| return output_text | |
| gr.Interface( | |
| fn=predict, | |
| inputs=["text", "text"], | |
| outputs=[ | |
| gr.Textbox(label="Generated definition") | |
| ], | |
| title="Word definition", | |
| description=description, | |
| ).launch() |