Update README.md

README.md

@@ -34,21 +34,22 @@ If you want to load the `module` weights into the main model, just remove the `-
 If multiple resolution are used, you need to add the `--multireso` and `--reso-step 64 ` parameter. 
 
 ```bash
-model='DiT-g/2'                                 # model type
-task_flag="lora_jade_ema_rank64"                # task flag 
-resume=./ckpts/t2i/model/                       # resume checkpoint 
-index_file=dataset/index_v2_json/jade.json      # index file
-results_dir=./log_EXP                           # save root for results
-batch_size=1                                    # training batch size  
-image_size=1024                                 # training image resolution
-grad_accu_steps=2                               # gradient accumulation steps 
-warmup_num_steps=0                              # warm-up steps
-lr=0.0001                                       # learning rate
-ckpt_every=100                                  # create a ckpt every a few steps.
-ckpt_latest_every=2000                          # create a ckpt named `latest.pt` every a few steps. 
-rank=64                                         # rank of lora 
-
-PYTHONPATH=./ deepspeed hydit/train_large_deepspeed.py \
+model='DiT-g/2'                                        # model type
+task_flag="lora_porcelain_ema_rank64"                  # task flag 
+resume=./ckpts/t2i/model/                              # resume checkpoint 
+index_file=dataset/porcelain/jsons/porcelain.json      # the selected data indices
+results_dir=./log_EXP                                  # save root for results
+batch_size=1                                           # training batch size
+image_size=1024                                        # training image resolution
+grad_accu_steps=2                                      # gradient accumulation steps
+warmup_num_steps=0                                     # warm-up steps
+lr=0.0001                                              # learning rate
+ckpt_every=100                                         # create a ckpt every a few steps.
+ckpt_latest_every=2000                                 # create a ckpt named `latest.pt` every a few steps.
+rank=64                                                # rank of lora
+max_training_steps=2000                                # Maximum training iteration steps
+
+PYTHONPATH=./ deepspeed hydit/train_deepspeed.py \
     --task-flag ${task_flag} \
     --model ${model} \
     --training_parts lora \
@@ -91,8 +92,8 @@ Recommended parameter settings
 |:---------------:|:---------:|:---------------------------------------------------:|:--:|
 |   `--batch_size` |    Training batch size    |        1        | Depends on GPU memory| 
 |   `--grad-accu-steps` |    Size of gradient accumulation    |       2        | - |
-|   `--rank` |    Rank of lora    |       64        | 8-128 are all possible|
-|   `--max-training-steps` |    Training steps  |       2000        | Varies with the amount of training data, about 2000 steps are enough for 100 images|
+|   `--rank` |    Rank of lora    |       64        | Choosing from 8-128|
+|   `--max-training-steps` |    Training steps  |       2000        | Depend on training data size, for reference apply 2000 steps on 100 images|
 |   `--lr` |    Learning rate  |        0.0001        | - |
 
 
@@ -107,7 +108,7 @@ Make sure you have activated the conda environment before running the following
 > We recommend not using prompt enhance, as it may lead to the disappearance of style words. 
 
 ```shell
-# porcelain style
+# jade style
 
 # By default, we start a Chinese UI.
 python app/hydit_app.py  --load-key ema --lora_ckpt ./ckpts/t2i/lora/jade
@@ -122,7 +123,7 @@ python app/hydit_app.py --no-enhance --load-key ema --lora_ckpt  ./ckpts/t2i/lor
 # Start with English UI
 python app/hydit_app.py --lang en --load-key ema --lora_ckpt ./ckpts/t2i/lora/jade
 
-# jade style 
+# porcelain style 
 
 # By default, we start a Chinese UI.
 python app/hydit_app.py  --load-key ema --lora_ckpt ./ckpts/t2i/lora/porcelain
@@ -144,7 +145,7 @@ python app/hydit_app.py --lang en --load-key ema --lora_ckpt ./ckpts/t2i/lora/po
 We provide several commands to quick start: 
 
 ```shell
-# porcelain style
+# jade style
 
 # Prompt Enhancement + Text-to-Image. Torch mode
 python sample_t2i.py --prompt "玉石绘画风格，一只猫在追蝴蝶" --load-key ema --lora_ckpt ./ckpts/t2i/lora/jade
@@ -158,7 +159,7 @@ python sample_t2i.py --infer-mode fa --prompt "玉石绘画风格，一只猫在
 # Generate an image with other image sizes.
 python sample_t2i.py --prompt "玉石绘画风格，一只猫在追蝴蝶" --image-size 1280 768 --load-key ema --lora_ckpt ./ckpts/t2i/lora/jade
 
-# jade style 
+# porcelain style 
 
 # Prompt Enhancement + Text-to-Image. Torch mode
 python sample_t2i.py --prompt "青花瓷风格，一只猫在追蝴蝶" --load-key ema --lora_ckpt ./ckpts/t2i/lora/porcelain