Update README.md

README.md

@@ -133,9 +133,78 @@ The Segmind Stable Diffusion Model is suitable for research and practical applic
 
 The Segmind Stable Diffusion Model can also be used directly with the 🧨 Diffusers library training scripts for further training, including:
 
-- **[Fine-Tune](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_sdxl.py)**
-- **[LoRA](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora_sdxl.py)**
-- **[Dreambooth LoRA](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_sdxl.py)**
+- **[Fine-Tune](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_sdxl.py):**
+```bash
+export MODEL_NAME="segmind/SSD-1B"
+export VAE_NAME="madebyollin/sdxl-vae-fp16-fix"
+export DATASET_NAME="lambdalabs/pokemon-blip-captions"
+
+accelerate launch train_text_to_image_lora_sdxl.py \
+  --pretrained_model_name_or_path=$MODEL_NAME \
+  --pretrained_vae_model_name_or_path=$VAE_NAME \
+  --dataset_name=$DATASET_NAME --caption_column="text" \
+  --resolution=1024 --random_flip \
+  --train_batch_size=1 \
+  --num_train_epochs=2 --checkpointing_steps=500 \
+  --learning_rate=1e-04 --lr_scheduler="constant" --lr_warmup_steps=0 \
+  --mixed_precision="fp16" \
+  --seed=42 \
+  --output_dir="sd-pokemon-model-lora-sdxl" \
+  --validation_prompt="cute dragon creature" --report_to="wandb" \
+  --push_to_hub
+```
+- **[LoRA](https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_lora_sdxl.py):**
+```bash
+export MODEL_NAME="segmind/SSD-1B"
+export VAE_NAME="madebyollin/sdxl-vae-fp16-fix"
+export DATASET_NAME="lambdalabs/pokemon-blip-captions"
+
+accelerate launch train_text_to_image_sdxl.py \
+  --pretrained_model_name_or_path=$MODEL_NAME \
+  --pretrained_vae_model_name_or_path=$VAE_NAME \
+  --dataset_name=$DATASET_NAME \
+  --enable_xformers_memory_efficient_attention \
+  --resolution=512 --center_crop --random_flip \
+  --proportion_empty_prompts=0.2 \
+  --train_batch_size=1 \
+  --gradient_accumulation_steps=4 --gradient_checkpointing \
+  --max_train_steps=10000 \
+  --use_8bit_adam \
+  --learning_rate=1e-06 --lr_scheduler="constant" --lr_warmup_steps=0 \
+  --mixed_precision="fp16" \
+  --report_to="wandb" \
+  --validation_prompt="a cute Sundar Pichai creature" --validation_epochs 5 \
+  --checkpointing_steps=5000 \
+  --output_dir="sdxl-pokemon-model" \
+  --push_to_hub
+```
+- **[Dreambooth LoRA](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_sdxl.py):**
+```bash
+export MODEL_NAME="segmind/SSD-1B"
+export INSTANCE_DIR="dog"
+export OUTPUT_DIR="lora-trained-xl"
+export VAE_PATH="madebyollin/sdxl-vae-fp16-fix"
+
+accelerate launch train_dreambooth_lora_sdxl.py \
+  --pretrained_model_name_or_path=$MODEL_NAME  \
+  --instance_data_dir=$INSTANCE_DIR \
+  --pretrained_vae_model_name_or_path=$VAE_PATH \
+  --output_dir=$OUTPUT_DIR \
+  --mixed_precision="fp16" \
+  --instance_prompt="a photo of sks dog" \
+  --resolution=1024 \
+  --train_batch_size=1 \
+  --gradient_accumulation_steps=4 \
+  --learning_rate=1e-5 \
+  --report_to="wandb" \
+  --lr_scheduler="constant" \
+  --lr_warmup_steps=0 \
+  --max_train_steps=500 \
+  --validation_prompt="A photo of sks dog in a bucket" \
+  --validation_epochs=25 \
+  --seed="0" \
+  --push_to_hub
+```
 
 ### Out-of-Scope Use