Spaces:
Running
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app.py
CHANGED
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import gradio as gr
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from convert_url_to_diffusers_multi_gr import convert_url_to_diffusers_repo, get_dtypes, FLUX_BASE_REPOS, SD35_BASE_REPOS
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from presets import (DEFAULT_DTYPE, schedulers, clips, t5s, sdxl_vaes, sdxl_loras, sdxl_preset_dict, sdxl_set_presets,
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sd15_vaes, sd15_loras, sd15_preset_dict, sd15_set_presets, flux_vaes, flux_loras, flux_preset_dict, flux_set_presets,
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sd35_vaes, sd35_loras, sd35_preset_dict, sd35_set_presets)
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import os
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HF_USER = os.getenv("HF_USER", "")
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HF_REPO = os.getenv("HF_REPO", "")
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HF_URL = os.getenv("HF_URL", "")
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HF_OW = os.getenv("HF_OW", False)
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HF_PR = os.getenv("HF_PR", False)
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css = """
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.title { font-size: 3em; align-items: center; text-align: center; }
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.info { align-items: center; text-align: center; }
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.block.result { margin: 1em 0; padding: 1em; box-shadow: 0 0 3px 3px #664422, 0 0 3px 2px #664422 inset; border-radius: 6px; background: #665544; }
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"""
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with gr.Blocks(theme="
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gr.Markdown("# Download SDXL / SD 1.5 / SD 3.5 / FLUX.1 safetensors and convert to HF🤗 Diffusers format and create your repo", elem_classes="title")
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gr.Markdown(f"""
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### ⚠️IMPORTANT NOTICE⚠️<br>
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It's dangerous to expose your access token or key to others.
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If you do use it, I recommend that you duplicate this space on your own HF account in advance.
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Keys and tokens could be set to **Secrets** (`HF_TOKEN`, `CIVITAI_API_KEY`) if it's placed in your own space.
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It saves you the trouble of typing them in.<br>
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It barely works in the CPU space, but larger files can be converted if duplicated on the more powerful **Zero GPU** space.
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In particular, conversion of FLUX.1 or SD 3.5 is almost impossible in CPU space.
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### The steps are the following:
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1. Paste a write-access token from [hf.co/settings/tokens](https://huggingface.co/settings/tokens).
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1. Input a model download url of the Hugging Face or Civitai or other sites.
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1. If you want to download a model from Civitai, paste a Civitai API Key.
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1. Input your HF user ID. e.g. 'yourid'.
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1. Input your new repo name. If empty, auto-complete. e.g. 'newrepo'.
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1. Set the parameters. If not sure, just use the defaults.
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1. Click "Submit".
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1. Patiently wait until the output changes. It takes approximately 2 to 3 minutes (on SDXL models downloading from HF).
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""")
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with gr.Column():
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dl_url = gr.Textbox(label="URL to download", placeholder="https://huggingface.co/bluepen5805/blue_pencil-XL/blob/main/blue_pencil-XL-v7.0.0.safetensors",
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value=HF_URL, max_lines=1)
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with gr.Group():
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with gr.Row():
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hf_user = gr.Textbox(label="Your HF user ID", placeholder="username", value=HF_USER, max_lines=1)
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hf_repo = gr.Textbox(label="New repo name", placeholder="reponame", info="If empty, auto-complete", value=HF_REPO, max_lines=1)
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with gr.Row(equal_height=True):
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with gr.Column():
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hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1)
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gr.Markdown("Your token is available at [hf.co/settings/tokens](https://huggingface.co/settings/tokens).", elem_classes="info")
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with gr.Column():
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civitai_key = gr.Textbox(label="Your Civitai API Key (Optional)", info="If you download model from Civitai...", placeholder="", value="", max_lines=1)
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gr.Markdown("Your Civitai API key is available at [https://civitai.com/user/account](https://civitai.com/user/account).", elem_classes="info")
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with gr.Row():
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is_upload_sf = gr.Checkbox(label="Upload single safetensors file into new repo", value=False)
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is_private = gr.Checkbox(label="Create private repo", value=True)
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with gr.Column():
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outputs=[
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outputs=[
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import gradio as gr
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from convert_url_to_diffusers_multi_gr import convert_url_to_diffusers_repo, get_dtypes, FLUX_BASE_REPOS, SD35_BASE_REPOS
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from presets import (DEFAULT_DTYPE, schedulers, clips, t5s, sdxl_vaes, sdxl_loras, sdxl_preset_dict, sdxl_set_presets,
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sd15_vaes, sd15_loras, sd15_preset_dict, sd15_set_presets, flux_vaes, flux_loras, flux_preset_dict, flux_set_presets,
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sd35_vaes, sd35_loras, sd35_preset_dict, sd35_set_presets)
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import os
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HF_USER = os.getenv("HF_USER", "")
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HF_REPO = os.getenv("HF_REPO", "")
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HF_URL = os.getenv("HF_URL", "")
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HF_OW = os.getenv("HF_OW", False)
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HF_PR = os.getenv("HF_PR", False)
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css = """
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.title { font-size: 3em; align-items: center; text-align: center; }
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.info { align-items: center; text-align: center; }
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.block.result { margin: 1em 0; padding: 1em; box-shadow: 0 0 3px 3px #664422, 0 0 3px 2px #664422 inset; border-radius: 6px; background: #665544; }
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"""
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with gr.Blocks(theme="theNeofr/Syne", fill_width=True, css=css, delete_cache=(60, 3600)) as demo:
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gr.Markdown("# Download SDXL / SD 1.5 / SD 3.5 / FLUX.1 safetensors and convert to HF🤗 Diffusers format and create your repo", elem_classes="title")
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gr.Markdown(f"""
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### ⚠️IMPORTANT NOTICE⚠️<br>
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+
It's dangerous to expose your access token or key to others.
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+
If you do use it, I recommend that you duplicate this space on your own HF account in advance.
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+
Keys and tokens could be set to **Secrets** (`HF_TOKEN`, `CIVITAI_API_KEY`) if it's placed in your own space.
|
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+
It saves you the trouble of typing them in.<br>
|
| 29 |
+
It barely works in the CPU space, but larger files can be converted if duplicated on the more powerful **Zero GPU** space.
|
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+
In particular, conversion of FLUX.1 or SD 3.5 is almost impossible in CPU space.
|
| 31 |
+
### The steps are the following:
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1. Paste a write-access token from [hf.co/settings/tokens](https://huggingface.co/settings/tokens).
|
| 33 |
+
1. Input a model download url of the Hugging Face or Civitai or other sites.
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1. If you want to download a model from Civitai, paste a Civitai API Key.
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1. Input your HF user ID. e.g. 'yourid'.
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1. Input your new repo name. If empty, auto-complete. e.g. 'newrepo'.
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1. Set the parameters. If not sure, just use the defaults.
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1. Click "Submit".
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1. Patiently wait until the output changes. It takes approximately 2 to 3 minutes (on SDXL models downloading from HF).
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""")
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with gr.Column():
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dl_url = gr.Textbox(label="URL to download", placeholder="https://huggingface.co/bluepen5805/blue_pencil-XL/blob/main/blue_pencil-XL-v7.0.0.safetensors",
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value=HF_URL, max_lines=1)
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with gr.Group():
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with gr.Row():
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hf_user = gr.Textbox(label="Your HF user ID", placeholder="username", value=HF_USER, max_lines=1)
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hf_repo = gr.Textbox(label="New repo name", placeholder="reponame", info="If empty, auto-complete", value=HF_REPO, max_lines=1)
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with gr.Row(equal_height=True):
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with gr.Column():
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hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1)
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gr.Markdown("Your token is available at [hf.co/settings/tokens](https://huggingface.co/settings/tokens).", elem_classes="info")
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with gr.Column():
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civitai_key = gr.Textbox(label="Your Civitai API Key (Optional)", info="If you download model from Civitai...", placeholder="", value="", max_lines=1)
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gr.Markdown("Your Civitai API key is available at [https://civitai.com/user/account](https://civitai.com/user/account).", elem_classes="info")
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with gr.Row():
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is_upload_sf = gr.Checkbox(label="Upload single safetensors file into new repo", value=False)
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is_private = gr.Checkbox(label="Create private repo", value=True)
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with gr.Row():
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is_overwrite = gr.Checkbox(label="Overwrite repo", value=HF_OW)
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is_pr = gr.Checkbox(label="Create PR", value=HF_PR)
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with gr.Tab("SDXL"):
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with gr.Group():
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sdxl_presets = gr.Radio(label="Presets", choices=list(sdxl_preset_dict.keys()), value=list(sdxl_preset_dict.keys())[0])
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sdxl_mtype = gr.Textbox(value="SDXL", visible=False)
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with gr.Row():
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sdxl_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE)
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with gr.Accordion("Advanced settings", open=False):
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with gr.Row():
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sdxl_vae = gr.Dropdown(label="VAE", choices=sdxl_vaes, value="", allow_custom_value=True)
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sdxl_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
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sdxl_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler a")
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with gr.Row():
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with gr.Column():
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with gr.Row():
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sdxl_lora1 = gr.Dropdown(label="LoRA1", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320)
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sdxl_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
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with gr.Column():
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with gr.Row():
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sdxl_lora2 = gr.Dropdown(label="LoRA2", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320)
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sdxl_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
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with gr.Column():
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with gr.Row():
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sdxl_lora3 = gr.Dropdown(label="LoRA3", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320)
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sdxl_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
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with gr.Column():
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with gr.Row():
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sdxl_lora4 = gr.Dropdown(label="LoRA4", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320)
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sdxl_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
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with gr.Column():
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with gr.Row():
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sdxl_lora5 = gr.Dropdown(label="LoRA5", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320)
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sdxl_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
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sdxl_run_button = gr.Button(value="Submit", variant="primary")
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with gr.Tab("SD 1.5"):
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with gr.Group():
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with gr.Row():
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sd15_presets = gr.Radio(label="Presets", choices=list(sd15_preset_dict.keys()), value=list(sd15_preset_dict.keys())[0])
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with gr.Row():
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sd15_mtype = gr.Textbox(value="SD 1.5", visible=False)
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with gr.Row():
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sd15_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE)
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with gr.Row():
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sd15_ema = gr.Checkbox(label="Extract EMA", value=True, visible=True)
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with gr.Row():
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sd15_isize = gr.Radio(label="Image size", choices=["768", "512"], value="768")
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with gr.Row():
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sd15_sc = gr.Checkbox(label="Safety checker", value=False)
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with gr.Accordion("Advanced settings", open=False):
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with gr.Row():
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sd15_vae = gr.Dropdown(label="VAE", choices=sd15_vaes, value="", allow_custom_value=True)
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with gr.Row():
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sd15_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
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with gr.Row():
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sd15_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler")
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with gr.Row():
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with gr.Column():
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with gr.Row():
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| 118 |
+
sd15_lora1 = gr.Dropdown(label="LoRA1", choices=sd15_loras, value="", allow_custom_value=True, min_width=320)
|
| 119 |
+
with gr.Row():
|
| 120 |
+
sd15_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
|
| 121 |
+
with gr.Row():
|
| 122 |
+
with gr.Column():
|
| 123 |
+
sd15_lora2 = gr.Dropdown(label="LoRA2", choices=sd15_loras, value="", allow_custom_value=True, min_width=320)
|
| 124 |
+
with gr.Row():
|
| 125 |
+
sd15_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
|
| 126 |
+
with gr.Column():
|
| 127 |
+
with gr.Row():
|
| 128 |
+
sd15_lora3 = gr.Dropdown(label="LoRA3", choices=sd15_loras, value="", allow_custom_value=True, min_width=320)
|
| 129 |
+
with gr.Row():
|
| 130 |
+
sd15_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
|
| 131 |
+
|
| 132 |
+
with gr.Column():
|
| 133 |
+
with gr.Row():
|
| 134 |
+
sd15_lora4 = gr.Dropdown(label="LoRA4", choices=sd15_loras, value="", allow_custom_value=True, min_width=320)
|
| 135 |
+
with gr.Row():
|
| 136 |
+
sd15_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
|
| 137 |
+
with gr.Column():
|
| 138 |
+
with gr.Row():
|
| 139 |
+
sd15_lora5 = gr.Dropdown(label="LoRA5", choices=sd15_loras, value="", allow_custom_value=True, min_width=320)
|
| 140 |
+
with gr.Row():
|
| 141 |
+
sd15_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
|
| 142 |
+
sd15_run_button = gr.Button(value="Submit", variant="primary")
|
| 143 |
+
with gr.Tab("FLUX.1"):
|
| 144 |
+
with gr.Group():
|
| 145 |
+
flux_presets = gr.Radio(label="Presets", choices=list(flux_preset_dict.keys()), value=list(flux_preset_dict.keys())[0])
|
| 146 |
+
flux_mtype = gr.Textbox(value="FLUX", visible=False)
|
| 147 |
+
with gr.Row():
|
| 148 |
+
flux_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16")
|
| 149 |
+
flux_base_repo = gr.Dropdown(label="Base repo ID", choices=FLUX_BASE_REPOS, value=FLUX_BASE_REPOS[0], allow_custom_value=True, visible=True)
|
| 150 |
+
with gr.Accordion("Advanced settings", open=False):
|
| 151 |
+
with gr.Row():
|
| 152 |
+
flux_vae = gr.Dropdown(label="VAE", choices=flux_vaes, value="", allow_custom_value=True)
|
| 153 |
+
with gr.Row():
|
| 154 |
+
flux_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
|
| 155 |
+
with gr.Row():
|
| 156 |
+
flux_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True)
|
| 157 |
+
flux_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False)
|
| 158 |
+
with gr.Row():
|
| 159 |
+
with gr.Column():
|
| 160 |
+
flux_lora1 = gr.Dropdown(label="LoRA1", choices=flux_loras, value="", allow_custom_value=True, min_width=320)
|
| 161 |
+
flux_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
|
| 162 |
+
with gr.Column():
|
| 163 |
+
flux_lora2 = gr.Dropdown(label="LoRA2", choices=flux_loras, value="", allow_custom_value=True, min_width=320)
|
| 164 |
+
flux_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
|
| 165 |
+
with gr.Column():
|
| 166 |
+
flux_lora3 = gr.Dropdown(label="LoRA3", choices=flux_loras, value="", allow_custom_value=True, min_width=320)
|
| 167 |
+
flux_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
|
| 168 |
+
with gr.Column():
|
| 169 |
+
flux_lora4 = gr.Dropdown(label="LoRA4", choices=flux_loras, value="", allow_custom_value=True, min_width=320)
|
| 170 |
+
flux_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
|
| 171 |
+
with gr.Column():
|
| 172 |
+
flux_lora5 = gr.Dropdown(label="LoRA5", choices=flux_loras, value="", allow_custom_value=True, min_width=320)
|
| 173 |
+
flux_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
|
| 174 |
+
flux_run_button = gr.Button(value="Submit", variant="primary")
|
| 175 |
+
with gr.Tab("SD 3.5"):
|
| 176 |
+
with gr.Group():
|
| 177 |
+
with gr.Row():
|
| 178 |
+
sd35_presets = gr.Radio(label="Presets", choices=list(sd35_preset_dict.keys()), value=list(sd35_preset_dict.keys())[0])
|
| 179 |
+
with gr.Row():
|
| 180 |
+
sd35_mtype = gr.Textbox(value="SD 3.5", visible=False)
|
| 181 |
+
with gr.Row():
|
| 182 |
+
sd35_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16")
|
| 183 |
+
sd35_base_repo = gr.Dropdown(label="Base repo ID", choices=SD35_BASE_REPOS, value=SD35_BASE_REPOS[0], allow_custom_value=True, visible=True)
|
| 184 |
+
with gr.Accordion("Advanced settings", open=False):
|
| 185 |
+
with gr.Row():
|
| 186 |
+
sd35_vae = gr.Dropdown(label="VAE", choices=sd35_vaes, value="", allow_custom_value=True)
|
| 187 |
+
sd35_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True)
|
| 188 |
+
sd35_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True)
|
| 189 |
+
sd35_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False)
|
| 190 |
+
with gr.Row():
|
| 191 |
+
with gr.Column():
|
| 192 |
+
with gr.Row():
|
| 193 |
+
sd35_lora1 = gr.Dropdown(label="LoRA1", choices=sd35_loras, value="", allow_custom_value=True, min_width=320)
|
| 194 |
+
sd35_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale")
|
| 195 |
+
with gr.Column():
|
| 196 |
+
with gr.Row():
|
| 197 |
+
sd35_lora2 = gr.Dropdown(label="LoRA2", choices=sd35_loras, value="", allow_custom_value=True, min_width=320)
|
| 198 |
+
sd35_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale")
|
| 199 |
+
with gr.Column():
|
| 200 |
+
with gr.Row():
|
| 201 |
+
sd35_lora3 = gr.Dropdown(label="LoRA3", choices=sd35_loras, value="", allow_custom_value=True, min_width=320)
|
| 202 |
+
sd35_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale")
|
| 203 |
+
with gr.Column():
|
| 204 |
+
with gr.Row():
|
| 205 |
+
sd35_lora4 = gr.Dropdown(label="LoRA4", choices=sd35_loras, value="", allow_custom_value=True, min_width=320)
|
| 206 |
+
sd35_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale")
|
| 207 |
+
with gr.Column():
|
| 208 |
+
with gr.Row():
|
| 209 |
+
sd35_lora5 = gr.Dropdown(label="LoRA5", choices=sd35_loras, value="", allow_custom_value=True, min_width=320)
|
| 210 |
+
sd35_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale")
|
| 211 |
+
sd35_run_button = gr.Button(value="Submit", variant="primary")
|
| 212 |
+
adv_args = gr.Textbox(label="Advanced arguments", value="", visible=False)
|
| 213 |
+
with gr.Group():
|
| 214 |
+
with gr.Row():
|
| 215 |
+
repo_urls = gr.CheckboxGroup(visible=False, choices=[], value=[])
|
| 216 |
+
output_md = gr.Markdown(label="Output", value="<br><br>", elem_classes="result")
|
| 217 |
+
clear_button = gr.Button(value="Clear Output", variant="secondary")
|
| 218 |
+
gr.DuplicateButton(value="Duplicate Space")
|
| 219 |
+
|
| 220 |
+
gr.Markdown("This webui was redesigned with ❤ by [theNeofr](https://huggingface.co/theNeofr)")
|
| 221 |
+
gr.on(
|
| 222 |
+
triggers=[sdxl_run_button.click],
|
| 223 |
+
fn=convert_url_to_diffusers_repo,
|
| 224 |
+
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, is_overwrite, is_pr, is_upload_sf, repo_urls,
|
| 225 |
+
sdxl_dtype, sdxl_vae, sdxl_clip, flux_t5, sdxl_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sdxl_mtype,
|
| 226 |
+
sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s, sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s, adv_args],
|
| 227 |
+
outputs=[repo_urls, output_md],
|
| 228 |
+
)
|
| 229 |
+
sdxl_presets.change(
|
| 230 |
+
fn=sdxl_set_presets,
|
| 231 |
+
inputs=[sdxl_presets],
|
| 232 |
+
outputs=[sdxl_dtype, sdxl_vae, sdxl_scheduler, sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s,
|
| 233 |
+
sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s],
|
| 234 |
+
queue=False,
|
| 235 |
+
)
|
| 236 |
+
gr.on(
|
| 237 |
+
triggers=[sd15_run_button.click],
|
| 238 |
+
fn=convert_url_to_diffusers_repo,
|
| 239 |
+
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, is_overwrite, is_pr, is_upload_sf, repo_urls,
|
| 240 |
+
sd15_dtype, sd15_vae, sd15_clip, flux_t5, sd15_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sd15_mtype,
|
| 241 |
+
sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s, sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, adv_args],
|
| 242 |
+
outputs=[repo_urls, output_md],
|
| 243 |
+
)
|
| 244 |
+
sd15_presets.change(
|
| 245 |
+
fn=sd15_set_presets,
|
| 246 |
+
inputs=[sd15_presets],
|
| 247 |
+
outputs=[sd15_dtype, sd15_vae, sd15_scheduler, sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s,
|
| 248 |
+
sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, sd15_ema],
|
| 249 |
+
queue=False,
|
| 250 |
+
)
|
| 251 |
+
gr.on(
|
| 252 |
+
triggers=[flux_run_button.click],
|
| 253 |
+
fn=convert_url_to_diffusers_repo,
|
| 254 |
+
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, is_overwrite, is_pr, is_upload_sf, repo_urls,
|
| 255 |
+
flux_dtype, flux_vae, flux_clip, flux_t5, flux_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, flux_mtype,
|
| 256 |
+
flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s, flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, adv_args],
|
| 257 |
+
outputs=[repo_urls, output_md],
|
| 258 |
+
)
|
| 259 |
+
flux_presets.change(
|
| 260 |
+
fn=flux_set_presets,
|
| 261 |
+
inputs=[flux_presets],
|
| 262 |
+
outputs=[flux_dtype, flux_vae, flux_scheduler, flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s,
|
| 263 |
+
flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, flux_base_repo],
|
| 264 |
+
queue=False,
|
| 265 |
+
)
|
| 266 |
+
gr.on(
|
| 267 |
+
triggers=[sd35_run_button.click],
|
| 268 |
+
fn=convert_url_to_diffusers_repo,
|
| 269 |
+
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, is_overwrite, is_pr, is_upload_sf, repo_urls,
|
| 270 |
+
sd35_dtype, sd35_vae, sd35_clip, sd35_t5, sd35_scheduler, sd15_ema, sd15_isize, sd15_sc, sd35_base_repo, sd35_mtype,
|
| 271 |
+
sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s, sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, adv_args],
|
| 272 |
+
outputs=[repo_urls, output_md],
|
| 273 |
+
)
|
| 274 |
+
sd35_presets.change(
|
| 275 |
+
fn=sd35_set_presets,
|
| 276 |
+
inputs=[sd35_presets],
|
| 277 |
+
outputs=[sd35_dtype, sd35_vae, sd35_scheduler, sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s,
|
| 278 |
+
sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, sd35_base_repo],
|
| 279 |
+
queue=False,
|
| 280 |
+
)
|
| 281 |
+
clear_button.click(lambda: ([], "<br><br>"), None, [repo_urls, output_md], queue=False, show_api=False)
|
| 282 |
+
|
| 283 |
+
demo.queue()
|
| 284 |
+
demo.launch()
|