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from __future__ import annotations |
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import pathlib |
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import gradio as gr |
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import slugify |
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from constants import UploadTarget |
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from uploader import Uploader |
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from utils import find_exp_dirs |
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class LoRAModelUploader(Uploader): |
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def upload_lora_model( |
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self, |
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folder_path: str, |
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repo_name: str, |
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upload_to: str, |
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private: bool, |
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delete_existing_repo: bool, |
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) -> str: |
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if not repo_name: |
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repo_name = pathlib.Path(folder_path).name |
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repo_name = slugify.slugify(repo_name) |
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if upload_to == UploadTarget.PERSONAL_PROFILE.value: |
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organization = '' |
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elif upload_to == UploadTarget.LORA_LIBRARY.value: |
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organization = 'lora-library' |
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else: |
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raise ValueError |
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return self.upload(folder_path, |
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repo_name, |
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organization=organization, |
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private=private, |
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delete_existing_repo=delete_existing_repo) |
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def load_local_lora_model_list() -> dict: |
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choices = find_exp_dirs(ignore_repo=True) |
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return gr.update(choices=choices, value=choices[0] if choices else None) |
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def create_upload_demo(hf_token: str | None) -> gr.Blocks: |
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uploader = LoRAModelUploader(hf_token) |
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model_dirs = find_exp_dirs(ignore_repo=True) |
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with gr.Blocks() as demo: |
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with gr.Box(): |
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gr.Markdown('Local Models') |
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reload_button = gr.Button('Reload Model List') |
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model_dir = gr.Dropdown( |
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label='Model names', |
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choices=model_dirs, |
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value=model_dirs[0] if model_dirs else None) |
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gr.Markdown( |
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'- Models uploaded in training time will not be shown here.') |
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with gr.Box(): |
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gr.Markdown('Upload Settings') |
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with gr.Row(): |
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use_private_repo = gr.Checkbox(label='Private', value=False) |
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delete_existing_repo = gr.Checkbox( |
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label='Delete existing repo of the same name', value=False) |
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upload_to = gr.Radio(label='Upload to', |
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choices=[_.value for _ in UploadTarget], |
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value=UploadTarget.PERSONAL_PROFILE.value) |
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model_name = gr.Textbox(label='Model Name') |
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upload_button = gr.Button('Upload') |
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gr.Markdown(''' |
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- You can upload your trained model to your personal profile (i.e. https://huggingface.co./{your_username}/{model_name}) or to the public [LoRA Concepts Library](https://huggingface.co./lora-library) (i.e. https://huggingface.co./lora-library/{model_name}). |
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''') |
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with gr.Box(): |
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gr.Markdown('Output message') |
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output_message = gr.Markdown() |
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reload_button.click(fn=load_local_lora_model_list, |
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inputs=None, |
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outputs=model_dir) |
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upload_button.click(fn=uploader.upload_lora_model, |
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inputs=[ |
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model_dir, |
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model_name, |
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upload_to, |
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use_private_repo, |
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delete_existing_repo, |
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], |
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outputs=output_message) |
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return demo |
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if __name__ == '__main__': |
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import os |
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hf_token = os.getenv('HF_TOKEN') |
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demo = create_upload_demo(hf_token) |
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demo.queue(max_size=1).launch(share=False) |
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