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Have you had any data check on the w2v dictionaries like the outliers? What is the range for all the embedding values? Do I need to normalize them?
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- asynchronous updates, i.e., HOGWILD
- multiple sgd runs ("chains"): this is easy to do using the `doParallel` package as it doesn't require any parallel tinkering in C++
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I use spacy's transformer model for other purposes (such as NER), so re-using the same model made sense.
Looks like Spacy made some tweaks to their syntax which are breaking KeyBERT's spacy backend.
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Hello @giannisnik, I was wondering whether we can apply the models here to samples that can be represented with multiple sets. For instance, document representation with each sentence as a bag. Thanks…
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As an additional model for the package. Use previous work from Dominik for the dataloaders.
Try to incorporate intensities instead of just thresholds.
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Hi, I am very interested in your work. I want to reproduce the experiment of CoNLL2003 english, but I don't have the 100-dimension Glove embeddings. Can you offer the 100-dimension Glove embeddings? …
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Why did I choose this paper? Because it analyzes the effect of tweet length on topic modeling methods.
### Main problem:
Which model is better for topic detection in the short text (tweet)?
Does …
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For ubertext 1.0 [we've used](https://lang.org.ua/uk/models/#anchor4) following algorithms:
- LexVec (it seems that now it works with subwords, yay!)
- Word2Vec
- GloVe
Params that was previou…
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Thanks for your excellent work. I have tried to combine multi personalized concepts for the inference. I saw in your paper that your codes can generate the "a photo of * in the style of @". But when I…
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1) Generate SenseGram models from 100 and 300 dimensinal word2vec embeddings generated from the ukWaC corpus. Use the ``uwac_2_cbow_100.text.model`` first.
2) Re-compute the unsupervised results …