Python 谷歌colab中的ScispaCy

我正在尝试使用colab中的ScispaCy建立NER临床数据模型。我已经安装了这样的软件包

!pip install spacy
!pip install scispacy
!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.2.4/en_core_sci_md-0.2.4.tar.gz       #pip install <Model URL>```

然后使用下面的代码显示句子和实体

nlp = spacy.load("en_core_sci_md")
text ="""Myeloid derived suppressor cells (MDSC) are immature myeloid cells with immunosuppressive activity. They accumulate in tumor-bearing mice and humans with different types of cancer, including hepatocellular carcinoma (HCC)""" 
doc = nlp(text)
print(list(doc.sents))
print(doc.ents)

我得到以下错误

OSError: [E050] Can't find model 'en_core_sci_md'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.

我不知道为什么会出现这个错误，我遵循了ScispaCy官方GitHub帖子中的所有代码。任何帮助都将不胜感激。

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提前谢谢。

我希望不会太晚。。。我相信你非常接近正确的方法

我会分步写我的答案，你可以选择停在哪里

步骤1）

步骤2）

步骤3）

步骤4）

步骤5）

步骤6）

步骤7）

OSError: [E050] Can't find model 'en_core_sci_md'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.

#Install en_core_sci_lg package from the website of spacy  (large corpus), but you can also use en_core_sci_md for the medium corpus.
       
!pip install https://s3-us-west-2.amazonaws.com/ai2-s2-scispacy/releases/v0.2.4/en_core_sci_lg-0.2.4.tar.gz 

# Import the large dataset
import en_core_sci_lg

# Identify entities
nlp = en_core_sci_lg.load()
doc = nlp(text)
displacy_image = displacy.render(doc, jupyter = True, style = "ent")

#Print only the entities
print(doc.ents)

# Save the result 
save_res = [doc.ents]
save_res

#Save the results to a dataframe
df_save_res = pd.DataFrame(save_res)
df_save_res

# In case that you want to visualise the dependency parse
  displacy_image = displacy.render(doc, jupyter = True, style = "dep")