Neural-Style-Transfer-Papers VS Style-Transfer-in-Text

Compare Neural-Style-Transfer-Papers vs Style-Transfer-in-Text and see what are their differences.

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Neural-Style-Transfer-Papers Style-Transfer-in-Text
1 3
1,629 1,620
0.1% 0.2%
0.0 1.2
about 3 years ago about 2 years ago
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Neural-Style-Transfer-Papers

Posts with mentions or reviews of Neural-Style-Transfer-Papers. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-30.

Style-Transfer-in-Text

Posts with mentions or reviews of Style-Transfer-in-Text. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-01.

What are some alternatives?

When comparing Neural-Style-Transfer-Papers and Style-Transfer-in-Text you can also consider the following projects:

Faces2Anime - Faces2Anime: Cartoon Style Transfer in Faces using Generative Adversarial Networks. Masters Thesis 2021 @ NTUST.

awesome-refreshing-llms - EMNLP'23 survey: a curation of awesome papers and resources on refreshing large language models (LLMs) without expensive retraining.

git-quick-stats - ▁▅▆▃▅ Git quick statistics is a simple and efficient way to access various statistics in git repository.

gpt-2-simple - Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

Text_Style_Transfer_Survey - This repo collects the articles for text attribute transfer

arpa

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