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| import gradio as gr | |
| from convert import convert | |
| DESCRIPTION = """ | |
| The steps are the following: | |
| - Paste a read-access token from hf.co/settings/tokens. Read access is enough given that we will open a PR against the source repo. | |
| - Input a model id from the Hub | |
| - Input the filename from the root dir of the repo that you would like to convert, e.g. 'v2-1_768-ema-pruned.ckpt' or 'v1-5-pruned.safetensors' | |
| - Chose which Stable Diffusion version, image size, scheduler type the model has and whether you want the "ema", or "non-ema" weights. | |
| - Click "Submit" | |
| - That's it! You'll get feedback if it works or not, and if it worked, you'll get the URL of the opened PR 🔥 | |
| ⚠️ If you encounter weird error messages, please have a look into the Logs and feel free to open a PR to correct the error messages. | |
| """ | |
| demo = gr.Interface( | |
| title="Convert any Stable Diffusion checkpoint to Diffusers and open a PR", | |
| description=DESCRIPTION, | |
| allow_flagging="never", | |
| article="Check out the [Diffusers repo on GitHub](https://github.com/huggingface/diffusers)", | |
| inputs=[ | |
| gr.Text(max_lines=1, label="your_hf_token"), | |
| gr.Text(max_lines=1, label="model_id"), | |
| gr.Text(max_lines=1, label="filename"), | |
| gr.Radio(label="Model type", choices=["v1", "v2", "ControlNet"]), | |
| gr.Radio(label="Sample size (px)", choices=[512, 768]), | |
| gr.Radio(label="Scheduler type", choices=["pndm", "heun", "euler", "dpm", "ddim"], value="dpm"), | |
| gr.Radio(label="Extract EMA or non-EMA?", choices=["ema", "non-ema"], value="ema"), | |
| ], | |
| outputs=[gr.Markdown(label="output")], | |
| fn=convert, | |
| ).queue(max_size=10, concurrency_count=1) | |
| demo.launch(show_api=True) | |