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import gradio as gr | |
from convert_url_to_diffusers_multi_gr import convert_url_to_diffusers_repo, get_dtypes, FLUX_BASE_REPOS, SD35_BASE_REPOS | |
from presets import (DEFAULT_DTYPE, schedulers, clips, t5s, sdxl_vaes, sdxl_loras, sdxl_preset_dict, sdxl_set_presets, | |
sd15_vaes, sd15_loras, sd15_preset_dict, sd15_set_presets, flux_vaes, flux_loras, flux_preset_dict, flux_set_presets, | |
sd35_vaes, sd35_loras, sd35_preset_dict, sd35_set_presets) | |
import os | |
HF_USER = os.getenv("HF_USER", "") | |
HF_REPO = os.getenv("HF_REPO", "") | |
HF_URL = os.getenv("HF_URL", "") | |
HF_OW = os.getenv("HF_OW", False) | |
HF_PR = os.getenv("HF_PR", False) | |
css = """ | |
.title { font-size: 3em; align-items: center; text-align: center; } | |
.info { align-items: center; text-align: center; } | |
.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; } | |
""" | |
with gr.Blocks(theme="theNeofr/Syne", fill_width=True, css=css, delete_cache=(60, 3600)) as demo: | |
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") | |
gr.Markdown(f""" | |
### ⚠️IMPORTANT NOTICE⚠️<br> | |
It's dangerous to expose your access token or key to others. | |
If you do use it, I recommend that you duplicate this space on your own HF account in advance. | |
Keys and tokens could be set to **Secrets** (`HF_TOKEN`, `CIVITAI_API_KEY`) if it's placed in your own space. | |
It saves you the trouble of typing them in.<br> | |
It barely works in the CPU space, but larger files can be converted if duplicated on the more powerful **Zero GPU** space. | |
In particular, conversion of FLUX.1 or SD 3.5 is almost impossible in CPU space. | |
### The steps are the following: | |
1. Paste a write-access token from [hf.co/settings/tokens](https://huggingface.co/settings/tokens). | |
1. Input a model download url of the Hugging Face or Civitai or other sites. | |
1. If you want to download a model from Civitai, paste a Civitai API Key. | |
1. Input your HF user ID. e.g. 'yourid'. | |
1. Input your new repo name. If empty, auto-complete. e.g. 'newrepo'. | |
1. Set the parameters. If not sure, just use the defaults. | |
1. Click "Submit". | |
1. Patiently wait until the output changes. It takes approximately 2 to 3 minutes (on SDXL models downloading from HF). | |
""") | |
with gr.Column(): | |
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", | |
value=HF_URL, max_lines=1) | |
with gr.Group(): | |
with gr.Row(): | |
hf_user = gr.Textbox(label="Your HF user ID", placeholder="username", value=HF_USER, max_lines=1) | |
hf_repo = gr.Textbox(label="New repo name", placeholder="reponame", info="If empty, auto-complete", value=HF_REPO, max_lines=1) | |
with gr.Row(equal_height=True): | |
with gr.Column(): | |
hf_token = gr.Textbox(label="Your HF write token", placeholder="hf_...", value="", max_lines=1) | |
gr.Markdown("Your token is available at [hf.co/settings/tokens](https://huggingface.co/settings/tokens).", elem_classes="info") | |
with gr.Column(): | |
civitai_key = gr.Textbox(label="Your Civitai API Key (Optional)", info="If you download model from Civitai...", placeholder="", value="", max_lines=1) | |
gr.Markdown("Your Civitai API key is available at [https://civitai.com/user/account](https://civitai.com/user/account).", elem_classes="info") | |
with gr.Row(): | |
is_upload_sf = gr.Checkbox(label="Upload single safetensors file into new repo", value=False) | |
is_private = gr.Checkbox(label="Create private repo", value=True) | |
gated = gr.Radio(label="Create gated repo", info="Gated repo must be public", choices=["auto", "manual", "False"], value="False") | |
with gr.Row(): | |
is_overwrite = gr.Checkbox(label="Overwrite repo", value=HF_OW) | |
is_pr = gr.Checkbox(label="Create PR", value=HF_PR) | |
with gr.Tab("SDXL"): | |
with gr.Group(): | |
sdxl_presets = gr.Radio(label="Presets", choices=list(sdxl_preset_dict.keys()), value=list(sdxl_preset_dict.keys())[0]) | |
sdxl_mtype = gr.Textbox(value="SDXL", visible=False) | |
sdxl_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE) | |
with gr.Accordion("Advanced settings", open=False): | |
with gr.Row(): | |
sdxl_vae = gr.Dropdown(label="VAE", choices=sdxl_vaes, value="", allow_custom_value=True) | |
sdxl_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler a") | |
sdxl_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True) | |
with gr.Column(): | |
with gr.Row(): | |
sdxl_lora1 = gr.Dropdown(label="LoRA1", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sdxl_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale") | |
with gr.Row(): | |
sdxl_lora2 = gr.Dropdown(label="LoRA2", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sdxl_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale") | |
with gr.Row(): | |
sdxl_lora3 = gr.Dropdown(label="LoRA3", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sdxl_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale") | |
with gr.Row(): | |
sdxl_lora4 = gr.Dropdown(label="LoRA4", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sdxl_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale") | |
with gr.Row(): | |
sdxl_lora5 = gr.Dropdown(label="LoRA5", choices=sdxl_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sdxl_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale") | |
sdxl_run_button = gr.Button(value="Submit", variant="primary") | |
with gr.Tab("SD 1.5"): | |
with gr.Group(): | |
sd15_presets = gr.Radio(label="Presets", choices=list(sd15_preset_dict.keys()), value=list(sd15_preset_dict.keys())[0]) | |
sd15_mtype = gr.Textbox(value="SD 1.5", visible=False) | |
sd15_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value=DEFAULT_DTYPE) | |
with gr.Row(): | |
sd15_ema = gr.Checkbox(label="Extract EMA", value=True, visible=True) | |
sd15_isize = gr.Radio(label="Image size", choices=["768", "512"], value="768") | |
sd15_sc = gr.Checkbox(label="Safety checker", value=False) | |
with gr.Accordion("Advanced settings", open=False): | |
with gr.Row(): | |
sd15_vae = gr.Dropdown(label="VAE", choices=sd15_vaes, value="", allow_custom_value=True) | |
sd15_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=schedulers, value="Euler") | |
sd15_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True) | |
with gr.Column(): | |
with gr.Row(): | |
sd15_lora1 = gr.Dropdown(label="LoRA1", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd15_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale") | |
with gr.Row(): | |
sd15_lora2 = gr.Dropdown(label="LoRA2", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd15_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale") | |
with gr.Row(): | |
sd15_lora3 = gr.Dropdown(label="LoRA3", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd15_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale") | |
with gr.Row(): | |
sd15_lora4 = gr.Dropdown(label="LoRA4", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd15_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale") | |
with gr.Row(): | |
sd15_lora5 = gr.Dropdown(label="LoRA5", choices=sd15_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd15_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale") | |
sd15_run_button = gr.Button(value="Submit", variant="primary") | |
with gr.Tab("FLUX.1"): | |
with gr.Group(): | |
flux_presets = gr.Radio(label="Presets", choices=list(flux_preset_dict.keys()), value=list(flux_preset_dict.keys())[0]) | |
flux_mtype = gr.Textbox(value="FLUX", visible=False) | |
flux_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16") | |
flux_base_repo = gr.Dropdown(label="Base repo ID", choices=FLUX_BASE_REPOS, value=FLUX_BASE_REPOS[0], allow_custom_value=True, visible=True) | |
with gr.Accordion("Advanced settings", open=False): | |
with gr.Row(): | |
flux_vae = gr.Dropdown(label="VAE", choices=flux_vaes, value="", allow_custom_value=True) | |
flux_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False) | |
with gr.Row(): | |
flux_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True) | |
flux_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True) | |
with gr.Column(): | |
with gr.Row(): | |
flux_lora1 = gr.Dropdown(label="LoRA1", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
flux_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale") | |
with gr.Row(): | |
flux_lora2 = gr.Dropdown(label="LoRA2", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
flux_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale") | |
with gr.Row(): | |
flux_lora3 = gr.Dropdown(label="LoRA3", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
flux_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale") | |
with gr.Row(): | |
flux_lora4 = gr.Dropdown(label="LoRA4", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
flux_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale") | |
with gr.Row(): | |
flux_lora5 = gr.Dropdown(label="LoRA5", choices=flux_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
flux_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale") | |
flux_run_button = gr.Button(value="Submit", variant="primary") | |
with gr.Tab("SD 3.5"): | |
with gr.Group(): | |
sd35_presets = gr.Radio(label="Presets", choices=list(sd35_preset_dict.keys()), value=list(sd35_preset_dict.keys())[0]) | |
sd35_mtype = gr.Textbox(value="SD 3.5", visible=False) | |
sd35_dtype = gr.Radio(label="Output data type", choices=get_dtypes(), value="bf16") | |
sd35_base_repo = gr.Dropdown(label="Base repo ID", choices=SD35_BASE_REPOS, value=SD35_BASE_REPOS[0], allow_custom_value=True, visible=True) | |
with gr.Accordion("Advanced settings", open=False): | |
with gr.Row(): | |
sd35_vae = gr.Dropdown(label="VAE", choices=sd35_vaes, value="", allow_custom_value=True) | |
sd35_scheduler = gr.Dropdown(label="Scheduler (Sampler)", choices=[""], value="", visible=False) | |
with gr.Row(): | |
sd35_clip = gr.Dropdown(label="CLIP", choices=clips, value="", allow_custom_value=True) | |
sd35_t5 = gr.Dropdown(label="T5", choices=t5s, value="", allow_custom_value=True) | |
with gr.Column(): | |
with gr.Row(): | |
sd35_lora1 = gr.Dropdown(label="LoRA1", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd35_lora1s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA1 weight scale") | |
with gr.Row(): | |
sd35_lora2 = gr.Dropdown(label="LoRA2", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd35_lora2s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA2 weight scale") | |
with gr.Row(): | |
sd35_lora3 = gr.Dropdown(label="LoRA3", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd35_lora3s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA3 weight scale") | |
with gr.Row(): | |
sd35_lora4 = gr.Dropdown(label="LoRA4", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd35_lora4s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA4 weight scale") | |
with gr.Row(): | |
sd35_lora5 = gr.Dropdown(label="LoRA5", choices=sd35_loras, value="", allow_custom_value=True, min_width=320, scale=2) | |
sd35_lora5s = gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label="LoRA5 weight scale") | |
sd35_run_button = gr.Button(value="Submit", variant="primary") | |
adv_args = gr.Textbox(label="Advanced arguments", value="", visible=False) | |
with gr.Group(): | |
repo_urls = gr.CheckboxGroup(visible=False, choices=[], value=[]) | |
output_md = gr.Markdown(label="Output", value="<br><br>", elem_classes="result") | |
clear_button = gr.Button(value="Clear Output", variant="secondary") | |
gr.DuplicateButton(value="Duplicate Space") | |
gr.Markdown("This webui was redesigned with ❤ by [theNeofr](https://huggingface.co/theNeofr)") | |
gr.on( | |
triggers=[sdxl_run_button.click], | |
fn=convert_url_to_diffusers_repo, | |
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls, | |
sdxl_dtype, sdxl_vae, sdxl_clip, flux_t5, sdxl_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sdxl_mtype, | |
sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s, sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s, adv_args], | |
outputs=[repo_urls, output_md], | |
) | |
sdxl_presets.change( | |
fn=sdxl_set_presets, | |
inputs=[sdxl_presets], | |
outputs=[sdxl_dtype, sdxl_vae, sdxl_scheduler, sdxl_lora1, sdxl_lora1s, sdxl_lora2, sdxl_lora2s, sdxl_lora3, sdxl_lora3s, | |
sdxl_lora4, sdxl_lora4s, sdxl_lora5, sdxl_lora5s], | |
queue=False, | |
) | |
gr.on( | |
triggers=[sd15_run_button.click], | |
fn=convert_url_to_diffusers_repo, | |
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls, | |
sd15_dtype, sd15_vae, sd15_clip, flux_t5, sd15_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, sd15_mtype, | |
sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s, sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, adv_args], | |
outputs=[repo_urls, output_md], | |
) | |
sd15_presets.change( | |
fn=sd15_set_presets, | |
inputs=[sd15_presets], | |
outputs=[sd15_dtype, sd15_vae, sd15_scheduler, sd15_lora1, sd15_lora1s, sd15_lora2, sd15_lora2s, sd15_lora3, sd15_lora3s, | |
sd15_lora4, sd15_lora4s, sd15_lora5, sd15_lora5s, sd15_ema], | |
queue=False, | |
) | |
gr.on( | |
triggers=[flux_run_button.click], | |
fn=convert_url_to_diffusers_repo, | |
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls, | |
flux_dtype, flux_vae, flux_clip, flux_t5, flux_scheduler, sd15_ema, sd15_isize, sd15_sc, flux_base_repo, flux_mtype, | |
flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s, flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, adv_args], | |
outputs=[repo_urls, output_md], | |
) | |
flux_presets.change( | |
fn=flux_set_presets, | |
inputs=[flux_presets], | |
outputs=[flux_dtype, flux_vae, flux_scheduler, flux_lora1, flux_lora1s, flux_lora2, flux_lora2s, flux_lora3, flux_lora3s, | |
flux_lora4, flux_lora4s, flux_lora5, flux_lora5s, flux_base_repo], | |
queue=False, | |
) | |
gr.on( | |
triggers=[sd35_run_button.click], | |
fn=convert_url_to_diffusers_repo, | |
inputs=[dl_url, hf_user, hf_repo, hf_token, civitai_key, is_private, gated, is_overwrite, is_pr, is_upload_sf, repo_urls, | |
sd35_dtype, sd35_vae, sd35_clip, sd35_t5, sd35_scheduler, sd15_ema, sd15_isize, sd15_sc, sd35_base_repo, sd35_mtype, | |
sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s, sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, adv_args], | |
outputs=[repo_urls, output_md], | |
) | |
sd35_presets.change( | |
fn=sd35_set_presets, | |
inputs=[sd35_presets], | |
outputs=[sd35_dtype, sd35_vae, sd35_scheduler, sd35_lora1, sd35_lora1s, sd35_lora2, sd35_lora2s, sd35_lora3, sd35_lora3s, | |
sd35_lora4, sd35_lora4s, sd35_lora5, sd35_lora5s, sd35_base_repo], | |
queue=False, | |
) | |
clear_button.click(lambda: ([], "<br><br>"), None, [repo_urls, output_md], queue=False, show_api=False) | |
demo.queue() | |
demo.launch(ssr_mode=False) | |