Awesome-CLIP VS dl-colab-notebooks

Compare Awesome-CLIP vs dl-colab-notebooks and see what are their differences.

Awesome-CLIP

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

dl-colab-notebooks

Try out deep learning models online on Google Colab (by styler00dollar)
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Awesome-CLIP dl-colab-notebooks
2 2
1,019 47
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0.0 0.0
9 months ago almost 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.

dl-colab-notebooks

Posts with mentions or reviews of dl-colab-notebooks. 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 dl-colab-notebooks 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.

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

ml-art-colabs - A list of Machine Learning Art Colabs

deep-daze - Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun