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Update README.md

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@@ -16,7 +16,7 @@ Model was trained with size 512 and 3 layers, dropout 0.5.
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  The procedure for installing the required software is described [by Karpathy](https://github.com/karpathy/char-rnn), torch is required, the code is written in lua. Be careful, versions of libraries written many years ago are used.
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  ```bash
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- th sample.lua lm_lstm_epoch19.14_0.6292.t7 -length 10000 -temperature 0.5 -primetext 'some text'
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  ```
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  ## Train data
@@ -30,4 +30,103 @@ In an era of winning Transformers, ancient RNN models seem archaic. But I see th
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  This model was created just or fun of students at the end of the course.
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  The procedure for installing the required software is described [by Karpathy](https://github.com/karpathy/char-rnn), torch is required, the code is written in lua. Be careful, versions of libraries written many years ago are used.
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  ```bash
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+ th sample.lua lm_lstm_epoch27.89_0.7387.t7 -length 10000 -temperature 0.5 -primetext 'some text'
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  ```
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  ## Train data
 
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  This model was created just or fun of students at the end of the course.
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+ ## Samples
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+ ### temperature 0.5
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+
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+ ```python
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+ some text] and re.search('<meta content=\"(.*)\" name=\"author\"></meta>", oneline):
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+ for line in a:
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+ if re.search('<w><ana lex=\"(.+)\" gr=\".+"></ana>(.+?)</w>', line):
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+ s = re.search(reg_adj, line)
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+ if r:
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+ k = re.search('<meta content="(.+?)" name="author">', txt))
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+ sentences = re.sub('</w>', '', s)
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+ with open('file.txt', 'a', encoding = 'utf-8') as f:
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+ f.write(i+' '+count_words(f)
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+ f.write('\n')
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+ f.write('Выполняется файлов в папке в нет
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+ можно сделеть слово слово в папка с цифрами в названии в папка с программой и папенается в тексте нет разной инит.')
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+ print('Творительный падеж, единственное число')
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+ elif word.endswith('ах') or word.endswith ('ям'):
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+ print('Poss
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+ ```
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+
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+ ### temperature 0.6
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+
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+ ```python
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+
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+ def noun_midles(words):
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+ print(result)
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+ def main():
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+ print('В тексте нет попыгамителись попытка слов в препинания в ланное не равно киличество файлов (' + str(arr))
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+ def main():
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+ maxi = max_pmi_any(s, 'answ')
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+ print(count_form(textik, dictionary)
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+ def main():
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+ forms = open_file()
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+ words = open_text(way_to_file)
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+ words = []
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+ for i in range(len(forms)):
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+ if '.'
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+ words += word.strip('.,!?//()":;/|\)\'»\n\t ')
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+ reg_author = '<meta content="(.+?)" name="author"'
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+ bigrams.append(f +'\t'+str(pos[forms[i])+1
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+ else:
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+ dic[file] = 1
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+ else:
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+ d[key] = 1
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+ else:
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+ dic[key] = 1
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+ else:
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+ dic[lemmes[i]] += 1
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+ return d
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+ def write_out_count_forms(text):
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+ arr = re.findall('<w>(.+?)</w>', text)
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+ return text
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+ def find_max(string, 'words_anes)
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+
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+ ```
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+
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+ ### temperature 0.7
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+
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+ ```python
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+
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+ import re
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+ def main():
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+ maxi = max(pmi)
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+ number = int(input('Введите слово: ')
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+ if os.path.isfile(f):
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+ for key in d:
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+ f.write(key + '\n')
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+ f.close()
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+ return
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+ def main():
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+ text = text_process('text.txt')
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+ words = []
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+ words = []
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+ for word in words:
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+ word = word.strip('.,;:?!'))
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+ f.close()
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+ return forms
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+ def names_file(fname):
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+ with open (fname, 'r', encoding = 'utf-8') as f:
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+ text = f.read()
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+ return text
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+ def count_text(text):
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+ text2 = re.sub(u'<.*?></w>', text)
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+ return text
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+ def count_text(word, text):
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+ t = open_text(fname)
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+ return file
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+ def author('text.txt'):
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+ for i in range(len(reg)):
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+ forms[i] = words[i].strip('.,?!()*&^%$
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+ file[i] = file[i].strip('.,?!()*&^%$
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+ for k in range(len(list_)):
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+ if len(strings)>1:
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+ print('Олонаким препинания.html', 'a раздания')
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+ word=re.sub('<.*?>', '', word, text)
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+
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+
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+ ```