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import gradio as gr |
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from transformers import PegasusForConditionalGeneration |
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from tokenizers_pegasus import PegasusTokenizer |
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def summary(text): |
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model = PegasusForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Pegasus-238M-Summary-Chinese") |
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tokenizer = PegasusTokenizer.from_pretrained("IDEA-CCNL/Randeng-Pegasus-238M-Summary-Chinese") |
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inputs = tokenizer(text, max_length=1024, return_tensors="pt") |
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summary_ids = model.generate(inputs["input_ids"]) |
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return tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] |
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examples = ["电力数据是反映经济运行的“晴雨表”和“风向标”。今年以来，随着消费信心逐步回暖、企业复工开足马力生产，多地用电量整体呈现出积极信号。一起透过各地的用电量，来看看中国经济的发展态势。"] |
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iface = gr.Interface(fn=summary, inputs="text", outputs="text",examples=examples) |
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iface.launch() |
