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https://github.com/woctezuma/glide-text2im-colab

Colab notebook for openai/glide-text2im.
https://github.com/woctezuma/glide-text2im-colab

colab colab-notebook colab-notebooks colaboratory google-colab google-colab-gpu google-colab-notebook google-colab-notebooks google-colaboratory openai openai-glide openai-glide-text2im openai-text2im

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Colab notebook for openai/glide-text2im.

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README

          

# GLIDE text2im on Colab

This repository provides a Colab notebook to produce images conditioned on text prompts with [GLIDE][openai-glide-code] [1].

## Usage

- Run [`text2im.ipynb`][colab-notebook-text2im]
[![Open In Colab][colab-badge]][colab-notebook-text2im]

Tip: press `` to run everything.

## Results

The process is based on the small, filtered-data GLIDE model, with classifier-free guidance.

Results consist of 64x64 images, and the corresponding 256x256 upsampled versions.

Expected run-time: 2m30s (for the one-time set-up), 1 min (64x64 sampling), 30 sec (256x256 upsampling).

---

SampleSampleSample


Several uncurated samples obtained with the same prompt: "a magnificent French rooster singing".

## Safety considerations

The *small* model has 300 million parameters, compared to the unreleased 3.5 billion parameter model.

As described in Appendix F.1, the training dataset was *filtered* so that it would not contain:
- images of humans and human-like objects,
- images of violent objects,
- two prevalent hate symbols in America (swastika and confederate flag).

## References

[1] Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, et al. *GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models*. [arXiv preprint 2112.10741][openai-glide-paper]. 2021.

[openai-glide-code]:
[openai-glide-paper]:

[colab-notebook-text2im]:
[colab-badge]: