我已经训练了一个模型。现在我想导出它的输出类型（str）。我如何将它的输出结果保存在 Dataframe 或任何其他形式中，以便将来使用。

gf = df['findings'].astype(str) 
preprocess_text = gf.str.strip().replace("\n","") 
t5_prepared_Text = "summarize: "+preprocess_text print ("original text preprocessed: \n", preprocess_text) 
tokenized_text = tokenizer.encode(str(t5_prepared_Text, return_tensors="pt").to(device) 
# summmarize 
summary_ids = model.generate(tokenized_text, num_beams=4, no_repeat_ngram_size=2, min_length=30, max_length=100, early_stopping=True) 
output = tokenizer.decode(summary_ids[0], skip_special_tokens=True) print ("\n\nSummarized text: \n"

模型输出

0     summarize: There is XXXX increased opacity wit...
1     summarize: There is XXXX increased opacity wit...
2     summarize: There is XXXX increased opacity wit...
3     summarize: Interstitial markings are diffusely...
4     summarize: Interstitial markings are diffusely...
5                                        summarize: nan
6                                        summarize: nan
Name: findings, dtype: object:

到目前为止我已经试过这样

prediction = pd.DataFrame([text]).to_csv('prediction.csv')

但是它将所有这些行保存在csv的一个单元格（第一个单元格）中，并且都是如下所示的半形式。

0     summarize: There is XXXX increased opacity wit...
1     summarize: There is XXXX increased opacity wit...
2     summarize: There is XXXX increased opacity wit...
3     summarize: Interstitial markings are diffusely...
4     summarize: Interstitial markings are diffusely...
5                                        summarize: nan
6                                        summarize: nan
Name: findings, dtype: object: