zeinabkh / word_embedding

- preprocessing on Persian news use parsivar.
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help #1

Open Zheydari opened 2 years ago

Zheydari commented 2 years ago

سلام وقت بخیر خیلی از مطالب مفید شما استفاده کردم امیدوارم شما بتونید کمکم کنید من هنگام اجرای کد شما به این ارور بر میخورم Traceback (most recent call last): File "F:\code\hw2_word_embedding.py", line 184, in skip_embedding = skip_gram(news_list) File "F:\code\hw2_word_embedding.py", line 59, in skip_gram skip_gram = Word2Vec(docs_list,min_count=1,vector_size=300, workers=3, window =5, sg = 1) File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 427, in init self.train( File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 1042, in train self._check_training_sanity(epochs=epochs, total_examples=total_examples, total_words=total_words) File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 1540, in _check_training_sanity raise RuntimeError("you must first build vocabulary before training the model") RuntimeError: you must first build vocabulary before training the model

zeinabkh commented 2 years ago

سلام وقت شما هم بخیر، میشه لطفا از کدتون یه عکس بفرستید؟

On Tue, Jun 28, 2022 at 12:01 PM Zheydari @.***> wrote:

سلام وقت بخیر خیلی از مطالب مفید شما استفاده کردم امیدوارم شما بتونید کمکم کنید من هنگام اجرای کد شما به این ارور بر میخورم Traceback (most recent call last): File "F:\code\hw2_word_embedding.py", line 184, in skip_embedding = skip_gram(news_list) File "F:\code\hw2_word_embedding.py", line 59, in skip_gram skip_gram = Word2Vec(docs_list,min_count=1,vector_size=300, workers=3, window =5, sg = 1) File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 427, in init self.train( File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 1042, in train self._check_training_sanity(epochs=epochs, total_examples=total_examples, total_words=total_words) File "F:\pythonProject\lib\site-packages\gensim\models\word2vec.py", line 1540, in _check_training_sanity raise RuntimeError("you must first build vocabulary before training the model") RuntimeError: you must first build vocabulary before training the model

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