Quantization stable diffusion #84
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* CLIP score
* CLIP score * FID score * PickScore * install datasets torchmetrics
* chore serval python block to markdown * set seed to generator * install quanto
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@merveenoyan and @stevhliu can you give me some feedback about this PR |
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Really nice example of using the new quanto library! 👏
Some feedback:
- I'd refine the focus of the cookbook on using quanto to quantize a diffusion model. A clearer title could be
Quantize Stable Diffusion with quantobecause it tells you exactly what you're doing and with which library. - The "Step-by-Step Guide to Post Training Quantization (PTQ)" is kind of misleading because I thought this cookbook was going to walk through all the steps but it really only shows how to apply PTQ to the model and evaluate it against the base model. I would've liked to see more discussion around the other steps or just remove them entirely.
- I don't think you need to define the sections so granularly. It can be something simple like:
# Quantize Stable Diffusion with quanto
## Install and setup
## Base model
### Evaluation
## Quantized Stable Diffusion
### Evaluation- It'd also be nice to print out the results so you can directly see what the memory and execution time is as well as the image quality.
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I think you can very briefly explain the important steps of the process in a paragraph instead of putting like this
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this can be a simple markdown text and not a header (applies for many steps below
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@thliang01 thanks a lot for this recipe! from what I see it's in a very early stage, I left very general comments that should be applied to rest of the recipe. you can ask for review once it's ready for review. does this work? |
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nits: Stable Diffusion is an open-source image generation model*
It's a diffusion model that takes in text input and generates an image based on it.
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Nit: Installation
no need to make it a big header, we can even just say "We will install the necessary libraries for this tutorial".
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We can move imports whenever they're used to improve readability, so the reader doesn't have to go back up to remember which class or function comes from where
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let's again add more and more explanations of what we'll do instead of comments inside the code
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What does this PR do?
Fixes #83
Who can review?
Feel free to tag members/contributors who may be interested in your PR.