pycharm中运行transformers模型的坑（anaconda prompt命令行运行正常，pycharm却报错）

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已于 2023-07-23 14:57:38 修改

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分类专栏： pycharm AI大模型深度学习文章标签： python 深度学习 ai

于 2023-07-23 14:54:16 首次发布

本文链接：https://blog.youkuaiyun.com/m0_46861633/article/details/131879227

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博客主要讲述在Pycharm中运行transformers模型时遇到报错问题，而在Anaconda Prompt命令行运行正常。随后给出问题解决办法，展示修改后的代码，最终运行成功，同时提醒注意代码缩进。

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pycharm中运行transformers模型的坑（anaconda prompt命令行运行正常，pycharm却报错）

1、transformer示例

from transformers import pipeline

nlp = pipeline("question-answering")

context = "Extractive Question Answering is the task of extracting an answer from a text given a question. An example of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune a model on a SQuAD task, you may leverage the `run_squad.py`."

print(nlp(question="What is extractive question answering?", context=context))
print(nlp(question="What is a good example of a question answering dataset?", context=context))

报错

tranformers报错1
transformer报错2
但anaconda prompt运行正常
在这里插入图片描述

问题解决

在这里插入图片描述

修改后代码

from transformers import pipeline
if __name__ == '__main__':
    nlp = pipeline("question-answering")
    context = "Extractive Question Answering is the task of extracting an answer from a text given a question. An example of a question answering dataset is the SQuAD dataset, which is entirely based on that task. If you would like to fine-tune a model on a SQuAD task, you may leverage the `run_squad.py`."
    print(nlp(question="What is extractive question answering?", context=context))
    print(nlp(question="What is a good example of a question answering dataset?", context=context))

运行成功（注意缩进）