如何用Python语言在file.txt上从句子或数据训练中建立一元、二元、三元模型？

import nltk
from nltk import ngrams

# 读取file.txt文件
with open('file.txt', 'r') as file:
    text = file.read()

# 预处理文本
text = text.lower()  # 转换为小写
text = text.replace('.', '')  # 去除句号

# 分词
tokens = nltk.word_tokenize(text)

# 建立一元模型
unigrams = ngrams(tokens, 1)
unigram_model = nltk.FreqDist(unigrams)

# 建立二元模型
bigrams = ngrams(tokens, 2)
bigram_model = nltk.FreqDist(bigrams)

# 建立三元模型
trigrams = ngrams(tokens, 3)
trigram_model = nltk.FreqDist(trigrams)

# 打印模型结果
print("一元模型：")
for gram, freq in unigram_model.items():
    print(gram, freq)

print("二元模型：")
for gram, freq in bigram_model.items():
    print(gram, freq)

print("三元模型：")
for gram, freq in trigram_model.items():
    print(gram, freq)