import os import subprocess from huggingface_hub import HfApi, upload_folder import gradio as gr import hf_utils import utils subprocess.run(["git", "clone", "https://github.com/huggingface/diffusers.git", "diffs"]) def error_str(error, title="Error"): return f"""#### {title} {error}""" if error else "" def on_token_change(token): model_names, error = hf_utils.get_my_model_names(token) if model_names: model_names.append("Other") return gr.update(visible=bool(model_names)), gr.update(choices=model_names, value=model_names[0] if model_names else None), gr.update(value=error_str(error)) def url_to_model_id(model_id_str): return model_id_str.split("/")[-2] + "/" + model_id_str.split("/")[-1] if model_id_str.startswith("https://huggingface.co/") else model_id_str def get_ckpt_names(token, radio_model_names, input_model): model_id = url_to_model_id(input_model) if radio_model_names == "Other" else radio_model_names if token == "" or model_id == "": return error_str("Please enter both a token and a model name.", title="Invalid input"), gr.update(choices=[]), gr.update(visible=False) try: api = HfApi(token=token) ckpt_files = [f for f in api.list_repo_files(repo_id=model_id) if f.endswith(".ckpt")] if not ckpt_files: return error_str("No checkpoint files found in the model repo."), gr.update(choices=[]), gr.update(visible=False) return None, gr.update(choices=ckpt_files, value=ckpt_files[0], visible=True), gr.update(visible=True) except Exception as e: return error_str(e), gr.update(choices=[]), None def convert_and_push(radio_model_names, input_model, ckpt_name, token): model_id = url_to_model_id(input_model) if radio_model_names == "Other" else radio_model_names try: model_id = url_to_model_id(model_id) # 1. Download the checkpoint file ckpt_path, revision = hf_utils.download_file(repo_id=model_id, filename=ckpt_name, token=token) # 2. Run the conversion script os.makedirs(model_id) subprocess.run( [ "python3", "./diffs/scripts/convert_original_stable_diffusion_to_diffusers.py", "--checkpoint_path", ckpt_path, "--dump_path" , model_id, ] ) # 3. Push to the model repo commit_message="Add Diffusers weights" upload_folder( folder_path=model_id, repo_id=model_id, token=token, create_pr=True, commit_message=commit_message, commit_description=f"Add Diffusers weights converted from checkpoint `{ckpt_name}` in revision {revision}", ) # # 4. Delete the downloaded checkpoint file, yaml files, and the converted model folder hf_utils.delete_file(revision) subprocess.run(["rm", "-rf", model_id.split('/')[0]]) import glob for f in glob.glob("*.yaml*"): subprocess.run(["rm", "-rf", f]) return f"""Successfully converted the checkpoint and opened a PR to add the weights to the model repo. You can view and merge the PR [here]({hf_utils.get_pr_url(HfApi(token=token), model_id, commit_message)}).""" except Exception as e: return error_str(e) DESCRIPTION = """### Convert a stable diffusion checkpoint to Diffusers🧨 With this space, you can easily convert a CompVis stable diffusion checkpoint to Diffusers and automatically create a pull request to the model repo. You can choose to convert a checkpoint from one of your own models, or from any other model on the Hub.""" with gr.Blocks() as demo: gr.Markdown(DESCRIPTION) with gr.Row(): with gr.Column(scale=11): with gr.Column(): gr.Markdown("## 1. Load model info") input_token = gr.Textbox( max_lines=1, label="Enter your Hugging Face token", placeholder="READ permission is enough", ) gr.Markdown("You can get a token [here](https://huggingface.co/settings/tokens)") with gr.Group(visible=False) as group_model: radio_model_names = gr.Radio(label="Choose a model") input_model = gr.Textbox( max_lines=1, label="Model name or URL", placeholder="username/model_name", visible=False, ) btn_get_ckpts = gr.Button("Load") with gr.Column(scale=10): with gr.Column(visible=False) as group_convert: gr.Markdown("## 2. Convert to Diffusers🧨") radio_ckpts = gr.Radio(label="Choose the checkpoint to convert", visible=False) gr.Markdown("Conversion may take a few minutes.") btn_convert = gr.Button("Convert & Push") error_output = gr.Markdown(label="Output") input_token.change( fn=on_token_change, inputs=input_token, outputs=[group_model, radio_model_names, error_output], queue=False, scroll_to_output=True) radio_model_names.change( lambda x: gr.update(visible=x == "Other"), inputs=radio_model_names, outputs=input_model, queue=False, scroll_to_output=True) btn_get_ckpts.click( fn=get_ckpt_names, inputs=[input_token, radio_model_names, input_model], outputs=[error_output, radio_ckpts, group_convert], scroll_to_output=True, queue=False ) btn_convert.click( fn=convert_and_push, inputs=[radio_model_names, input_model, radio_ckpts, input_token], outputs=error_output, scroll_to_output=True ) # gr.Markdown("""""") gr.HTML("""