add sana-lora training files and update README.md;

Signed-off-by: lawrence-cj <[email protected]>

README.md

@@ -36,7 +36,7 @@ As a result, Sana-0.6B is very competitive with modern giant diffusion model (e.
 
 ## 🔥🔥 News
 
-- (🔥 New) \[2024/12/18\] `diffusers` supports Sana-LoRA fine-tuning! Sana-LoRA's training and convergence speed is supper fast. [\[Guidance\]](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sana.md). Thanks to [@paul](https://github.com/sayakpaul).
+- (🔥 New) \[2024/12/18\] `diffusers` supports Sana-LoRA fine-tuning! Sana-LoRA's training and convergence speed is supper fast. [\[Guidance\]](asset/docs/sana_lora_dreambooth.md) or  [\[diffusers docs\]](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sana.md).
 - (🔥 New) \[2024/12/13\] `diffusers` has Sana! [All Sana models in diffusers safetensors](https://huggingface.co/collections/Efficient-Large-Model/sana-673efba2a57ed99843f11f9e) are released and diffusers pipeline `SanaPipeline`, `SanaPAGPipeline`, `DPMSolverMultistepScheduler(with FlowMatching)` are all supported now. We prepare a [Model Card](asset/docs/model_zoo.md) for you to choose.
 - (🔥 New) \[2024/12/10\] 1.6B BF16 [Sana model](https://huggingface.co/Efficient-Large-Model/Sana_1600M_1024px_BF16) is released for stable fine-tuning.
 - (🔥 New) \[2024/12/9\] We release the [ComfyUI node](https://github.com/Efficient-Large-Model/ComfyUI_ExtraModels) for Sana. [\[Guidance\]](asset/docs/ComfyUI/comfyui.md)

asset/docs/sana_lora_dreambooth.md

@@ -22,12 +22,6 @@ cd diffusers
 pip install -e .
 ```
 
-Then cd in the `examples/dreambooth` folder and run
-
-```bash
-pip install -r requirements_sana.txt
-```
-
 And initialize an [🤗Accelerate](https://github.com/huggingface/accelerate/) environment with:
 
 ```bash
@@ -71,19 +65,29 @@ This will also allow us to push the trained LoRA parameters to the Hugging Face
 
 [Here is the Model Card](model_zoo.md) for you to choose the desired pre-trained models and set it to `MODEL_NAME`.
 
-Now, we can launch training using:
+Now, we can launch training using [file here](../../train_scripts/train_lora.sh):
 
 ```bash
+bash train_scripts/train_lora.sh
+```
+
+or you can run it locally:
+
+```bash
+huggingface-cli download diffusers/dog-example --local-dir data/dreambooth/dog --repo-type dataset
+
 export MODEL_NAME="Efficient-Large-Model/Sana_1600M_1024px_diffusers"
-export INSTANCE_DIR="dog"
+export INSTANCE_DIR="data/dreambooth/dog"
 export OUTPUT_DIR="trained-sana-lora"
 
-accelerate launch train_dreambooth_lora_sana.py \
+accelerate launch --num_processes 8 --main_process_port 29500 --gpu_ids 0,1,2,3 \
+  train_scripts/train_dreambooth_lora_sana.py \
   --pretrained_model_name_or_path=$MODEL_NAME  \
   --instance_data_dir=$INSTANCE_DIR \
   --output_dir=$OUTPUT_DIR \
   --mixed_precision="bf16" \
   --instance_prompt="a photo of sks dog" \
+  --mixed_precision="fp16" \
   --resolution=1024 \
   --train_batch_size=1 \
   --gradient_accumulation_steps=4 \