The training script contains all the parameters to help you customize your training run. These are found in the [`parse_args()`](https://github.com/huggingface/diffusers/blob/64603389da01082055a901f2883c4810d1144edb/examples/custom_diffusion/train_custom_diffusion.py#L319) function. The function comes with default values, but you can also set your own values in the training command if you'd like.  
For example, to change the resolution of the input image:  
```bash
accelerate launch train_custom_diffusion.py \
--resolution=256
```  
Many of the basic parameters are described in the [DreamBooth](dreambooth#script-parameters) training guide, so this guide focuses on the parameters unique to Custom Diffusion:  
- `--freeze_model`: freezes the key and value parameters in the cross-attention layer; the default is `crossattn_kv`, but you can set it to `crossattn` to train all the parameters in the cross-attention layer
- `--concepts_list`: to learn multiple concepts, provide a path to a JSON file containing the concepts
- `--modifier_token`: a special word used to represent the learned concept
- `--initializer_token`: a special word used to initialize the embeddings of the `modifier_token`
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/training/custom_diffusion.md