Merge branch 'sd3-flux.1' into dependabot/github_actions/crate-ci/typ…

…os-1.29.0

.dockerignore

@@ -3,6 +3,7 @@ cudnn_windows/
 bitsandbytes_windows/
 bitsandbytes_windows_deprecated/
 dataset/
+models/
 __pycache__/
 venv/
 **/.hadolint.yml

.github/workflows/docker_publish.yml

@@ -71,7 +71,7 @@ jobs:
           password: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Build and push
-        uses: docker/build-push-action@v5
+        uses: docker/build-push-action@v6
         id: publish
         with:
           context: .

.github/workflows/typos.yaml

@@ -18,4 +18,4 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: typos-action
-        uses: crate-ci/[email protected]
+        uses: crate-ci/[email protected]

.release

@@ -1 +1 @@
-v24.1.7
+v24.2.0

README.md

@@ -46,13 +46,19 @@ The GUI allows you to set the training parameters and generate and run the requi
       - [Potential Solutions](#potential-solutions)
   - [SDXL training](#sdxl-training)
   - [Masked loss](#masked-loss)
+  - [Guides](#guides)
+    - [Using Accelerate Lora Tab to Select GPU ID](#using-accelerate-lora-tab-to-select-gpu-id)
+      - [Starting Accelerate in GUI](#starting-accelerate-in-gui)
+      - [Running Multiple Instances (linux)](#running-multiple-instances-linux)
+      - [Monitoring Processes](#monitoring-processes)
+  - [Interesting Forks](#interesting-forks)
   - [Change History](#change-history)
 
 ## 🦒 Colab
 
 This Colab notebook was not created or maintained by me; however, it appears to function effectively. The source can be found at: <https://github.com/camenduru/kohya_ss-colab>.
 
-I would like to express my gratitude to camendutu for their valuable contribution. If you encounter any issues with the Colab notebook, please report them on their repository.
+I would like to express my gratitude to camenduru for their valuable contribution. If you encounter any issues with the Colab notebook, please report them on their repository.
 
 | Colab                                                                                                                                                                          | Info               |
 | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------ |
@@ -69,7 +75,7 @@ To install the necessary dependencies on a Windows system, follow these steps:
 1. Install [Python 3.10.11](https://www.python.org/ftp/python/3.10.11/python-3.10.11-amd64.exe).
    - During the installation process, ensure that you select the option to add Python to the 'PATH' environment variable.
 
-2. Install [CUDA 11.8 toolkit](https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Windows&target_arch=x86_64).
+2. Install [CUDA 12.4 toolkit](https://developer.nvidia.com/cuda-12-4-0-download-archive?target_os=Windows&target_arch=x86_64).
 
 3. Install [Git](https://git-scm.com/download/win).
 
@@ -127,7 +133,7 @@ To install the necessary dependencies on a Linux system, ensure that you fulfill
   apt install python3.10-venv
   ```
 
-- Install the CUDA 11.8 Toolkit by following the instructions provided in [this link](https://developer.nvidia.com/cuda-11-8-0-download-archive?target_os=Linux&target_arch=x86_64).
+- Install the CUDA 12.4 Toolkit by following the instructions provided in [this link](https://developer.nvidia.com/cuda-12-4-0-download-archive?target_os=Linux&target_arch=x86_64).
 
 - Make sure you have Python version 3.10.9 or higher (but lower than 3.11.0) installed on your system.
 
@@ -177,7 +183,7 @@ If you choose to use the interactive mode, the default values for the accelerate
 
 To install the necessary components for Runpod and run kohya_ss, follow these steps:
 
-1. Select the Runpod pytorch 2.0.1 template. This is important. Other templates may not work.
+1. Select the Runpod pytorch 2.2.0 template. This is important. Other templates may not work.
 
 2. SSH into the Runpod.
 
@@ -329,13 +335,27 @@ To upgrade your installation on Linux or macOS, follow these steps:
 To launch the GUI service, you can use the provided scripts or run the `kohya_gui.py` script directly. Use the command line arguments listed below to configure the underlying service.
 
 ```text
---listen: Specify the IP address to listen on for connections to Gradio.
---username: Set a username for authentication.
---password: Set a password for authentication.
---server_port: Define the port to run the server listener on.
---inbrowser: Open the Gradio UI in a web browser.
---share: Share the Gradio UI.
---language: Set custom language
+  --help                show this help message and exit
+  --config CONFIG       Path to the toml config file for interface defaults
+  --debug               Debug on
+  --listen LISTEN       IP to listen on for connections to Gradio
+  --username USERNAME   Username for authentication
+  --password PASSWORD   Password for authentication
+  --server_port SERVER_PORT
+                        Port to run the server listener on
+  --inbrowser           Open in browser
+  --share               Share the gradio UI
+  --headless            Is the server headless
+  --language LANGUAGE   Set custom language
+  --use-ipex            Use IPEX environment
+  --use-rocm            Use ROCm environment
+  --do_not_use_shell    Enforce not to use shell=True when running external commands
+  --do_not_share        Do not share the gradio UI
+  --requirements REQUIREMENTS
+                        requirements file to use for validation
+  --root_path ROOT_PATH
+                        `root_path` for Gradio to enable reverse proxy support. e.g. /kohya_ss
+  --noverify            Disable requirements verification
 ```
 
 ### Launching the GUI on Windows
@@ -438,6 +458,37 @@ The feature is not fully tested, so there may be bugs. If you find any issues, p
 
 ControlNet dataset is used to specify the mask. The mask images should be the RGB images. The pixel value 255 in R channel is treated as the mask (the loss is calculated only for the pixels with the mask), and 0 is treated as the non-mask. The pixel values 0-255 are converted to 0-1 (i.e., the pixel value 128 is treated as the half weight of the loss). See details for the dataset specification in the [LLLite documentation](./docs/train_lllite_README.md#preparing-the-dataset).
 
+## Guides
+
+The following are guides extracted from issues discussions
+
+### Using Accelerate Lora Tab to Select GPU ID
+
+#### Starting Accelerate in GUI
+
+- Open the kohya GUI on your desired port.
+- Open the `Accelerate launch` tab
+- Ensure the Multi-GPU checkbox is unchecked.
+- Set GPU IDs to the desired GPU (like 1).
+
+#### Running Multiple Instances (linux)
+
+- For tracking multiple processes, use separate kohya GUI instances on different ports (e.g., 7860, 7861).
+- Start instances using `nohup ./gui.sh --listen 0.0.0.0 --server_port <port> --headless > log.log 2>&1 &`.
+
+#### Monitoring Processes
+
+- Open each GUI in a separate browser tab.
+- For terminal access, use SSH and tools like `tmux` or `screen`.
+
+For more details, visit the [GitHub issue](https://github.com/bmaltais/kohya_ss/issues/2577).
+
+## Interesting Forks
+
+To finetune HunyuanDiT models or create LoRAs, visit this [fork](https://github.com/Tencent/HunyuanDiT/tree/main/kohya_ss-hydit)
+
 ## Change History
 
-See release information.
+Added support for SD3 (Dreambooth and Finetuning) and Flux.1 (Dreambooth, LoRA and Finetuning).
+
+See <https://github.com/kohya-ss/sd-scripts/blob/sd3/README.md> for more details.

_typos.toml

@@ -9,6 +9,7 @@ parms="parms"
 nin="nin"
 extention="extention" # Intentionally left
 nd="nd"
+pn="pn"
 shs="shs"
 sts="sts"
 scs="scs"