Colab notebook

I have slightly changed the structure of your text2im notebook so that:

• it runs straight away on Google Colab with GPU toggled ON,
• it is easier for everyone to try different prompts.

Run text2im.ipynb

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

[woctezuma]

I cannot reproduce the same results as showed in paper images “Figure 1” with the same text prompt.

Unfortunately, this is normal, because the publicly available model:

• is smaller, as it has roughly 10x fewer parameters,
• was trained on a filtered dataset.

You should get outputs similar to the third row of Figure 9.

From a user perspective, the main benefit of GLIDE is that it is much faster than the CLIP-guided methods which I have tried so far.

Is the base the only checkpoint available for the base diffusion model?

I think so. From what I can see in the code below, there are 6 checkpoints:

• two for classifier-free guidance (sampling and upsampling),
• two for inpainting (sampling and upsampling),
• two for CLIP (text encoding and image encoding).

https://github.com/openai/glide-text2im/blob/742510effd841c94d2130480f2c74d3b32dc2eb0/glide_text2im/download.py#L10-L17

[woctezuma]

I see the nice following commits:

• https://github.com/openai/glide-text2im/commit/146bd9c49a1bcf48541539af1344f09aca91893d add install command to notebooks -> git and pip at the start of the notebook,
• https://github.com/openai/glide-text2im/commit/f4689080ef35a10b6ad68902a6381d4b0feb5017 add colab links -> Colab badges for the links in the README,
• https://github.com/openai/glide-text2im/commit/9cc8e563851bd38f5ddb3e305127192cb0f02f5c colab GPU backend -> GPU support toggled ON.