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David Bielejeski 2022-09-27 09:25:28 -05:00
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@ -39,8 +39,41 @@ Now, if you wanna try to do this... please read the warnings below first:
- There doesn't seem to be an easy way to train two subjects consecutively. You will end up with an 11-12GB.
- I'm currently testing ways of compressing that down to ~2GB.
- You might have better luck training with `sd-v1-4-full-ema.ckpt`
- However, it's huge and it's annoying.
- ~~You might have better luck training with `sd-v1-4-full-ema.ckpt`~~
- Further testing has shown that it doesn't help.
- Best practice is to change the token to a celebrity name. Here's my wife trained with the exact same settings, except for the token:
The `ground truth` (real picture, caution: very beautiful woman)
<br><img src="https://user-images.githubusercontent.com/100188076/192403948-8d1d0e50-3e9f-495f-b8ba-1bcb6b536fc8.png" width="200">
Same prompt for all of these images below:
`sks`
<br><img src="https://user-images.githubusercontent.com/100188076/192403506-ab96c652-f7d0-47b0-98fa-267defa1e511.png" width="200">
`woman`
<br><img src="https://user-images.githubusercontent.com/100188076/192403491-cb258777-5091-4492-a6cc-82305fa729f4.png" width="200">
`Natalie Portman`
<br><img src="https://user-images.githubusercontent.com/100188076/192403437-f9a93720-d41c-4334-8901-fa2d2a10fe36.png" width="200">
`Kate Mara`
<br><img src="https://user-images.githubusercontent.com/100188076/192403461-1f6972d9-64d0-46b0-b2ed-737e47aae31e.png" width="200">
# RunPod Instructions
- Sign up for RunPod. Feel free to use my [referral link here](https://runpod.io?ref=n8yfwyum), so that I don't have to pay for it (but you do).
- Click **Deploy** on either `SECURE CLOUD` or `COMMUNITY CLOUD`
- Click `Select` on a GPU with at least 35 GB of VRAM (e.g. A100, A40, A6000, etc)
- Select a template > `Runpod / Stable Diffusion`
- Click `Connect` and choose `Jupyter Lab`
- Make a new notebook (it's just like Google Colab) and run the code below
```python
!git clone https://github.com/JoePenna/Dreambooth-Stable-Diffusion/
```
- With the file navigator on the left, `/workspace/Dreambooth-Stable-Diffusion/dreambooth_runpod_joepenna.ipynb` -- follow the instructions in there.
# Vast.AI Instructions
- Sign up for [Vast.AI](https://vast.ai/)
@ -64,18 +97,6 @@ Now, if you wanna try to do this... please read the warnings below first:
- ![img.png](readme-images/vast-ai-step6-open-notebook.png)
- Follow the instructions in the workbook and start training
# RunPod Instructions
- Sign up for RunPod. Feel free to use my [referral link here](https://runpod.io?ref=n8yfwyum), so that I don't have to pay for it (but you do).
- Click **Deploy** on either `SECURE CLOUD` or `COMMUNITY CLOUD`
- Click `Select` on a GPU with at least 35 GB of VRAM (e.g. A100, A40, A6000, etc)
- Select a template > `Runpod / Stable Diffusion`
- Click `Connect` and choose `Jupyter Lab`
- Make a new notebook (it's just like Google Colab) and run the code below
```python
!git clone https://github.com/JoePenna/Dreambooth-Stable-Diffusion/
```
- With the file navigator on the left, `/workspace/Dreambooth-Stable-Diffusion/dreambooth_runpod_joepenna.ipynb` -- follow the instructions in there.
# Original Readme from XavierXiao
This is an implementtaion of Google's [Dreambooth](https://arxiv.org/abs/2208.12242) with [Stable Diffusion](https://github.com/CompVis/stable-diffusion). The original Dreambooth is based on [Imagen](https://imagen.research.google/) text-to-image model. However, neither the model nor the pre-trained weights of Imagen is available. To enable people to fine-tune a text-to-image model with a few examples, I implemented the idea of Dreambooth on Stable diffusion.