Awesome-CLIP VS ml-art-colabs

Compare Awesome-CLIP vs ml-art-colabs and see what are their differences.

Awesome-CLIP

Awesome list for research on CLIP (Contrastive Language-Image Pre-Training). (by yzhuoning)

ml-art-colabs

A list of Machine Learning Art Colabs (by dvschultz)
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Awesome-CLIP ml-art-colabs
2 2
1,019 833
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0.0 1.8
9 months ago about 2 years ago
Jupyter Notebook
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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.

Awesome-CLIP

Posts with mentions or reviews of Awesome-CLIP. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-03.

ml-art-colabs

Posts with mentions or reviews of ml-art-colabs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-03.

What are some alternatives?

When comparing Awesome-CLIP and ml-art-colabs you can also consider the following projects:

Queryable - Run OpenAI's CLIP model on iOS to search photos.

awesome-pretrained-stylegan2 - A collection of pre-trained StyleGAN 2 models to download

Awesome-Text-to-Image - (ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.

dl-colab-notebooks - Try out deep learning models online on Google Colab

TediGAN - [CVPR 2021] Pytorch implementation for TediGAN: Text-Guided Diverse Face Image Generation and Manipulation. [Moved to: https://github.com/IIGROUP/TediGAN]