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This task is dependent on readiness of corpora tasks #1 , #2 , #4
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1. word2vec (cbow , skip-gram)
2. doc2vec (cbow , skip-gram)
ETC.
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Hey! I see that the gradient of the input layer is not being normalised by number of input tokens when training CBOW (same for skipgram when there are ngrams). Is there a reason behind it?
(I notice…
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I get a segmentation fault with high dimensions (600 or more) using cbow. A normal word2vec runs fine for this size but wang2vec does not. I am able to run wang2vec with skip.
here is the error:
…
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Node2vec and DeepWalk original proposals are built upon the skip-gram model. By default, nodevectors does not set the parameter ```w2vparams["sg"]``` to 1, therefore the underlying Word2Vec model uses…
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Need to restart Travis and Appveyor builds a couple of times in order to get this test set to pass. Is there a way to make it more robust?
-------------------- >> end captured logging > begin capture…
tmylk updated
7 years ago
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#### Problem description
I would like to fine-tune a fasttext embeddings model trained on wiki data on new in domain data,
I was using this code;
#### Steps/code/corpus to reproduce
model = Key…
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The link leads to google drive which I don't have right to access :(
Below is the excerpt
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You can download one or more models (833MB each) trained on [11.8GB English texts corpus](h…
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We should add Skip-list embedding as well as CBOW embedding.
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As for the recent paper "Learning Word Vectors for 157 Languages", the model CBOW is used with position dependent weights. Using that the new pre-trained model were produced.
Is it possible to train …