可以尝试调整模型的参数、增加训练数据或使用其他模型来解决重复输出的问题。还可以在处理输入数据时进行处理以避免与之前已生成的摘要重复。以下是一个Python代码示例，使用前需要自行更改相关参数：

from transformers import PegasusForConditionalGeneration, PegasusTokenizer

model_name = 'google/pegasus-bigbird-pubmed'
device = 'cuda' if torch.cuda.is_available() else 'cpu'
tokenizer = PegasusTokenizer.from_pretrained(model_name)
model = PegasusForConditionalGeneration.from_pretrained(model_name).to(device)

input_text = "输入文本"
input_ids = tokenizer.encode(input_text, return_tensors='pt').to(device)
output_ids = model.generate(input_ids, max_length=60, num_beams=5, length_penalty=0.6, early_stopping=True)

# 去除重复输出
unique_output = []
for output in output_ids.tolist():
    if output not in unique_output:
        unique_output.append(output)
        print(tokenizer.decode(output))