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README.md
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README.md
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[日本語版 README はこちら](README_ja.md)
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# Stable Diffusion Modal
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# Stable Diffusion CLI on Modal
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This is a Diffusers-based script for running Stable Diffusion on [Modal](https://modal.com/). It can perform txt2img inference and has the ability to increase resolution using ControlNet Tile and Upscaler.
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This is a Diffusers-based script for running Stable Diffusion on [Modal](https://modal.com/). This script has no WebUI and only works with CLI. It can perform txt2img inference and has the ability to increase resolution using ControlNet Tile and Upscaler.
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## Features
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@ -25,13 +25,13 @@ The app requires the following to run:
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The `modal-client` is the Python library. In order to install that:
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```
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```bash
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pip install modal-client
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```
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And you need a modal token to use this script:
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```
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```bash
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modal token new
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```
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@ -51,7 +51,7 @@ Images are generated and output to the `outputs/` directory.
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## Directory structure
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```
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```txt
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.
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├── .env # Secrets manager
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├── Makefile
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@ -73,7 +73,7 @@ Images are generated and output to the `outputs/` directory.
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### 1. `git clone` the repository
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```
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```bash
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git clone https://github.com/hodanov/stable-diffusion-modal.git
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cd stable-diffusion-modal
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```
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@ -84,53 +84,41 @@ Hugging Add hugging_face_token to .env file.
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This script downloads and uses a model from HuggingFace, but if you want to use a model in a private repository, you will need to set this environment variable.
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```
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```txt
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HUGGING_FACE_TOKEN="Write your hugging face token here."
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```
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### 3. Add the model to ./setup_files/config.yml
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Add the model used for inference. VAE, LoRA, and Textual Inversion are also configurable.
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Add the model used for inference. Use the Safetensors file as is. VAE, LoRA, and Textual Inversion are also configurable.
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```
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```yml
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# ex)
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model:
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name: stable-diffusion-2-1
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repo_id: stabilityai/stable-diffusion-2-1
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name: stable-diffusion-1-5
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url: https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned.safetensors # Specify URL for the safetensor file.
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vae:
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name: sd-vae-ft-mse
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repo_id: stabilityai/sd-vae-ft-mse
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url: https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors
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controlnets:
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- name: control_v11f1e_sd15_tile
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repo_id: lllyasviel/control_v11f1e_sd15_tile
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```
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Use a model configured for Diffusers, such as the one found in [this repository](https://huggingface.co/stabilityai/stable-diffusion-2-1). Files in safetensor format shared by Civitai etc. need to be converted (you can do so with a script in the diffusers official repository).
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If you want to use LoRA and Textual Inversion, configure as follows.
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[https://github.com/huggingface/diffusers/blob/main/scripts/convert_original_stable_diffusion_to_diffusers.py](https://github.com/huggingface/diffusers/blob/main/scripts/convert_original_stable_diffusion_to_diffusers.py)
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```
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# Example of using conversion script
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python ./diffusers/scripts/convert_original_stable_diffusion_to_diffusers.py --from_safetensors \
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--checkpoint_path="Write the filename of safetensor format here" \
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--dump_path="Write the output path here" \
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--device='cuda:0'
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```
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LoRA and Textual Inversion don't require any conversion and can directly use safetensors files. Add the download link to config.yml as below.
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```
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```yml
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# Example
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loras:
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- name: lora_name.safetensors # Specify the LoRA file name. Any name is fine, but the extension `.safetensors` is required.
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download_url: download_link_here # Specify the download link for the safetensor file.
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url: download_link_here # Specify the download link for the safetensor file.
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```
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### 4. Setting prompts
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Set the prompt to Makefile.
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```
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```makefile
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# ex)
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run:
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cd ./sdcli && modal run txt2img.py \
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@ -150,7 +138,7 @@ run:
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Execute the below command. An application will be deployed on Modal.
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```
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```bash
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make deploy
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```
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@ -158,7 +146,7 @@ make deploy
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The txt2img inference is executed with the following command.
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```
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```bash
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make run
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```
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52
README_ja.md
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README_ja.md
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# Stable Diffusion Modal
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# Stable Diffusion CLI on Modal
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[Modal](https://modal.com/)上でStable Diffusionを動かすためのDiffusersベースのスクリプトです。txt2imgの推論を実行することができ、ControlNet TileとUpscalerを利用した高解像度化の機能を備えています。
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[Modal](https://modal.com/)上でStable Diffusionを動かすためのDiffusersベースのスクリプトです。WebUIは無く、CLIでのみ動作します。txt2imgの推論を実行することができ、ControlNet TileとUpscalerを利用した高解像度化の機能を備えています。
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## このスクリプトでできること
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1. txt2imgによる画像生成ができます。
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2. アップスケーラーとControlNet Tileを利用した高解像度な画像を生成することができます。
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@ -27,13 +27,13 @@
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`modal-client`はModalをCLIから操作するためのPythonライブラリです。下記のようにインストールします:
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```
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```bash
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pip install modal-client
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```
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And you need a modal token to use this script:
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```
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```bash
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modal token new
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```
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@ -51,7 +51,7 @@ modal token new
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## ディレクトリ構成
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```
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```txt
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.
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├── .env # Secrets manager
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├── Makefile
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@ -73,7 +73,7 @@ modal token new
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### 1. リポジトリをgit cloneする
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```
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```bash
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git clone https://github.com/hodanov/stable-diffusion-modal.git
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cd stable-diffusion-modal
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```
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@ -84,53 +84,43 @@ Hugging FaceのトークンをHUGGING_FACE_TOKENに記入します。
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このスクリプトはHuggingFaceからモデルをダウンロードして使用しますが、プライベートリポジトリにあるモデルを参照する場合、この環境変数の設定が必要です。
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```
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```txt
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HUGGING_FACE_TOKEN="ここにHuggingFaceのトークンを記載する"
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```
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### 3. ./setup_files/config.ymlを設定する
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推論に使うモデルを設定します。VAE、LoRA、Textual Inversionも設定可能です。
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推論に使うモデルを設定します。Safetensorsファイルをそのまま利用します。VAE、LoRA、Textual Inversionも設定可能です。
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```
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下記のように、nameにモデル名、urlにSafetensorsファイルがあるURLを指定します。
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```yml
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# 設定例
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model:
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name: stable-diffusion-2-1 # モデル名を指定
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repo_id: stabilityai/stable-diffusion-2-1 # リポジトリのID（「プロファイル名/モデル名」の形で指定）
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name: stable-diffusion-1-5
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url: https://huggingface.co/runwayml/stable-diffusion-v1-5/blob/main/v1-5-pruned.safetensors # Specify URL for the safetensor file.
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vae:
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name: sd-vae-ft-mse
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repo_id: stabilityai/sd-vae-ft-mse
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url: https://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors
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controlnets:
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- name: control_v11f1e_sd15_tile
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repo_id: lllyasviel/control_v11f1e_sd15_tile
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```
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ModelとVAEは[こちらのリポジトリ](https://huggingface.co/stabilityai/stable-diffusion-2-1)にあるような、Diffusersのために構成されたモデルを利用します。Civitaiなどで共有されているsafetensors形式のファイルは変換が必要です（diffusersの公式リポジトリにあるスクリプトで変換できます）。
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LoRAは下記のように指定します。
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[変換スクリプト](https://github.com/huggingface/diffusers/blob/main/scripts/convert_original_stable_diffusion_to_diffusers.py)
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LoRAとTextual Inversionは変換不要で、safetensorsファイルをそのまま利用できます。
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```
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```yml
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# 設定例
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loras:
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- name: mecha.safetensors # ファイル名を指定。任意の名前で良いが、拡張子`.safetensors`は必須。
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download_url: https://civitai.com/api/download/models/150907?type=Model&format=SafeTensor # ダウンロードリンクを指定
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```
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```
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# 変換スクリプトの使用例
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python ./diffusers/scripts/convert_original_stable_diffusion_to_diffusers.py --from_safetensors \
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--checkpoint_path="ここに変換したいsafetensors形式のファイルを指定" \
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--dump_path="出力先を指定" \
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--device='cuda:0'
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url: https://civitai.com/api/download/models/150907?type=Model&format=SafeTensor # ダウンロードリンクを指定
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```
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### 4. Makefileの設定（プロンプトの設定）
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プロンプトをMakefileに設定します。
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```
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```makefile
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# 設定例
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run:
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cd ./sdcli && modal run txt2img.py \
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@ -160,7 +150,7 @@ run:
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下記のコマンドでModal上にアプリケーションが構築されます。
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```
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```bash
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make deploy
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```
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@ -168,6 +158,6 @@ make deploy
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下記のコマンドでtxt2img推論が実行されます。
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```
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```bash
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make run
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```
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