VAE training sample script

examples/vae/README.md

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+# Training a VAE
+
+Creating a training image set is [described in a different document](https://huggingface.co/docs/datasets/image_process#image-datasets).
+
+## Installing the dependencies
+
+Before running the scripts, make sure to install the library's training dependencies:
+
+**Important**
+
+To make sure you can successfully run the latest versions of the example scripts, we highly recommend **installing from source** and keeping the install up to date as we update the example scripts frequently and install some example-specific requirements. To do this, execute the following steps in a new virtual environment:
+```bash
+git clone https://github.com/huggingface/diffusers
+cd diffusers
+pip install .
+```
+
+Then cd in the example folder and run
+```bash
+pip install -r requirements.txt
+```
+
+## Training
+
+The command to train a VAE model on a custom dataset (`DATASET_NAME`):
+
+```bash
+python train_vae.py --mixed_precision="no" \
+ --pretrained_model_name_or_path="stabilityai/stable-diffusion-2-1" \
+ --dataset_name="<DATASET_NAME>" \
+ --train_batch_size=1 \
+ --gradient_accumulation_steps=4 \
+ --gradient_checkpointing
+ --report_to="wandb"
+```
+
+
+## Using the VAE
+
+

examples/vae/requirements.txt

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+lpips