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feat(nlp-spacy/ex5): update specifications and audit question
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@ -84,7 +84,7 @@ The goal of this exercise is to learn to tokenize a document using `spaCy`. We d
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The goal of this exercise is to learn to use `spaCy` embedding on a document.
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1. Compute the embedding of all the words in this sentence. The language model considered is `en_core_web_md`
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1. Compute the embedding of all the words in this sentence. The language model considered is `en_core_web_md` version 3.4.1.
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```
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"laptop computer coffee tea water liquid dog cat kitty"
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@ -48,14 +48,10 @@
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##### The exercise is validated if all questions of the exercise are validated
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###### For question 1, have the embeddings of each word a shape of `(300,)` and are the first 20 values of the embedding of laptop the following?
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###### For question 1, have the embeddings of each word a shape of `(300,)` and is the sum of the first 20 values of the embedding of laptop the following?
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```
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array([-0.37639 , -0.075521, 0.4908 , 0.19863 , -0.11088 , -0.076145,
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-0.30367 , -0.69663 , 0.87048 , 0.54388 , 0.42523 , 0.18045 ,
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-0.4358 , -0.32606 , -0.70702 , -0.069127, -0.42674 , 2.4147 ,
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0.26806 , 0.46584 ], dtype=float32)
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5.710388
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```
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###### For question 2, is the output the following?
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