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spacy Arabic word2vector
Yes, spaCy does offer pre-trained word vectors for Arabic as part of its language models. The default Arabic language model in spaCy is called “ar_core_news_md”, and it includes pre-trained word vectors that were trained on a large corpus of Arabic text.
To use the pre-trained word vectors, you can load the Arabic language model in spaCy and then access the word vectors for individual tokens in a text. Here’s an example:
import spacy nlp = spacy.load("ar_core_news_md") doc = nlp("أهلاً بالعالم") # Access the vector for the first token in the text vector = doc.vector print(vector)
This will output a 300-dimensional vector that represents the word “أهلاً”. You can access the word vectors for other tokens in the text by indexing into the
doc object with different integer values.
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