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Merge pull request #27 from damian0815/hf-download-docs 

documentation for the huggingface automatic downloader
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@ -4,28 +4,35 @@ In order to train, you need a base model on which to train. This is a one-time
Make sure the trainer is installed properly first. See [SETUP.md](SETUP.md) for more details.
When you finish you should see something like this, come back to reference this picture as you go through the steps below:
You can either [download one manually](#manual-download), or alternatively EveryDream2 can [automatically download](#automatic-download) a model from the Hugging Face hub for you.
## Manual download
First you have to download a `.ckpt` file for the base model, then you need to convert it to a "diffusers format" folder. When you finish you should see something like this, come back to reference this picture as you go through the steps below:
![models](ckptcache.png) *(this picture is just an EXAMPLE)*
## Download models
### Downloading the .ckpt
You need some sort of base model to start training. I suggest these two:
I suggest one of these two models:
Stable Diffusion 1.5 with improved VAE:
* Stable Diffusion 1.5 with improved VAE:
https://huggingface.co/panopstor/EveryDream/blob/main/sd_v1-5_vae.ckpt
https://huggingface.co/panopstor/EveryDream/blob/main/sd_v1-5_vae.ckpt
SD2.1 768:
https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/v2-1_768-nonema-pruned.ckpt
* SD2.1 768:
You can use SD2.0 512 as well, but typically SD1.5 is going to be better.
https://huggingface.co/stabilityai/stable-diffusion-2-1/blob/main/v2-1_768-nonema-pruned.ckpt
https://huggingface.co/stabilityai/stable-diffusion-2-base/blob/main/512-base-ema.ckpt
* You can use SD2.0 512 as well, but typically SD1.5 is going to be better.
https://huggingface.co/stabilityai/stable-diffusion-2-base/blob/main/512-base-ema.ckpt
Place these in the root folder of EveryDream2.
### Converting to 🧨diffusers format
Run these commands *one time* to prepare them. **It's very important to use the correct YAML!**
For SD1.x models, use this (note it will spill a lot of warnings to the console, but its fine):
@ -68,3 +75,52 @@ ex.
python train.py --resume_ckpt "v2-1_768-ema-pruned" ...
python train.py --resume_ckpt "512-base-ema" ...
## Automatic download
If you don't want the hassle of downloading and converting ckpt files, you can pass a Hugging Face "repo id" for `--resume-ckpt` and the model will be automatically downloaded from Huggingface if it exists.
For example, to use [Stable Diffusion 2.1](https://huggingface.co/stabilityai/stable-diffusion-2-1), you can pass the repo id `stabilityai/stable-diffusion-2-1` for `--resume_ckpt`:
python train.py --resume_ckpt stabilityai/stable-diffusion-2-1 ...
You can use any model on Huggingface which is saved in 🧨diffusers format, which is the vast majority of models on [this list](https://huggingface.co/models?pipeline_tag=text-to-image&sort=downloads). For example, to resume training using [nitrosocke's Modern Disney model](https://huggingface.co/nitrosocke/mo-di-diffusion) as a starting point, use `nitrosocke/mo-di-diffusion` as the repo id:
python train.py --resume_ckpt nitrosocke/mo-di-diffusion ...
You can check if a 🧨diffusers format model is available by checking [the "Files" tab](https://huggingface.co/nitrosocke/mo-di-diffusion/tree/main) for a bunch of folders with names like `feature_extractor`, `unet`, and `vae`.
### Hugging Face login
If the model requires you to sign a license agreement, you may need to login to the Hugging Face hub before downloads will work. You can do this by running the following command in the terminal window before you start training:
huggingface-cli login
When prompted, paste a [Hugging Face User Access Token](https://huggingface.co/settings/tokens) into the terminal window (you may not see anything appear to show that you've pasted something), and then press Enter.
> To get an Access Token you'll need to [create a Hugging Face account](https://huggingface.co/join) if you don't have one already. Login to your account and click `New token` on [your User Access Tokens page](https://huggingface.co/settings/tokens) to create an Access Token that you can then copy and paste into the terminal window.
> Note that on Windows you may have to right-click the terminal window -> Paste, rather than just using ctrl-V. You also may not see anything appear in the terminal to indicate that you've pasted something - just press Enter anyway. If downloading doesn't work after setting a token, double-check you have agreed to the license agreement and try running `huggingface-cli login` again.
**Alternatively**, you can set the environment variable `HF_API_TOKEN` to your Access Token. On Windows:
set HF_API_TOKEN=<token>
On Linux:
export HF_API_TOKEN=<token>
Replace `<token>` with the Access Token you got from [your Hugging Face User Access Tokens page](https://huggingface.co/settings/tokens)
### Where are the files?
By default the downloaded Hugging Face files are stored in the Hugging Face cache folder. On Windows this is at `C:\Users\username.cache\huggingface\hub`. On Linux it is at `~/.cache/huggingface/hub`.
You can set the environment variable `HUGGINGFACE_HUB_CACHE` to change this. Eg, to put the cache on `Z:\stable-diffusion-big-files\huggingface-hub-cache` (on Windows):
set HUGGINGFACE_HUB_CACHE=Z:\stable-diffusion-big-files\huggingface-hub-cache\
Make sure to do this before running `train.py`.
### Downloading from a subfolder
If the model you want to download is not stored in the root folder under the huggingface repo id, you can pass `--hf_repo_subfolder` to set the subfolder where it should be downloaded from.