Update README.md

README.md

@@ -253,7 +253,7 @@ This produces a JSON file in the ```instance_data_dir``` directory:
 {"file_name": "94.jpg", "prompt": "<leaf microstructure>, arafed image of a green plant with a yellow cross"}
 ```
 
-```raw
+```python
 !accelerate launch train_dreambooth_lora_sdxl.py \
   --pretrained_model_name_or_path="{pretrained_model_name_or_path}" \
   --pretrained_vae_model_name_or_path="{pretrained_vae_model_name_or_path}"\
@@ -277,4 +277,51 @@ This produces a JSON file in the ```instance_data_dir``` directory:
   --max_train_steps=500 \
   --checkpointing_steps=500 \
   --seed="0"
+```
+
+### With prior preservation 
+
+Set `--with_prior_preservation` flag to include prior preservation. In this case you must specify `--class_data_dir` (directory with class images) and `--class_prompt` (class prompt). You should also set `--num_class_images` to specify how many class preservation images you want to use. Either place them in the directory (specified via `--class_data_dir`) or the code with auto-generate them based off the base model. You can also provide a few yourself and let the code generate the remaining ones. 
+
+An example is provided below, commented out. The code that will run here will NOT use prior preservation. 
+
+Some other useful parameters that can be set include:
+
+--rank: LoRA adapter rank (LoRA alpha will be set identical to rank)
+--use_dora: Set if you want to use DORA
+
+Type ```python train_dreambooth_lora_sdxl.py``` to get a full list of parameters
+
+```python
+instance_data_dir = 'local_instance_data_dir'
+class_prompt      = 'a prompt that describes the images in the directory local_instance_data_dir'
+num_class_images  = 10 #how many images you want in this class
+
+!\accelerate launch train_dreambooth_lora_sdxl.py \
+  --pretrained_model_name_or_path="{pretrained_model_name_or_path}" \
+  --pretrained_vae_model_name_or_path="{pretrained_vae_model_name_or_path}"\
+  --dataset_name="{instance_data_dir}" \
+  --class_prompt="{class_prompt}" \
+  --num_class_images={num_class_images} \
+  --with_prior_preservation \
+  --class_data_dir="{class_data_dir}" \
+  --output_dir="{instance_output_dir}" \
+  --caption_column="prompt"\
+  --mixed_precision="fp16" \
+  --instance_prompt="{instance_prompt}" \
+  --validation_prompt="{val_prompt}" \
+  --validation_epochs={val_epochs} \
+  --resolution=1024 \
+  --train_batch_size=1 \
+  --gradient_accumulation_steps=4 \
+  --gradient_checkpointing \
+  --learning_rate=1e-4 \
+  --snr_gamma=5.0 \
+  --lr_scheduler="constant" \
+  --lr_warmup_steps=0 \
+  --mixed_precision="fp16" \
+  --use_8bit_adam \
+  --max_train_steps=500 \
+  --checkpointing_steps=500 \
+  --seed="0"
 ```