Spaces:
Running
on
Zero
Running
on
Zero
Upload 2 files
Browse files
app.py
CHANGED
@@ -221,7 +221,7 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
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triggers=[generate_button.click, prompt.submit],
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fn=change_base_model,
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inputs=[model_name],
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-
outputs=
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).success(
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fn=run_lora,
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inputs=[prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height,
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@@ -229,7 +229,7 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
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outputs=[result, seed]
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)
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-
model_name.change(change_base_model, [model_name],
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gr.on(
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triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit],
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triggers=[generate_button.click, prompt.submit],
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fn=change_base_model,
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inputs=[model_name],
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+
outputs=[result]
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).success(
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fn=run_lora,
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inputs=[prompt, cfg_scale, steps, selected_index, randomize_seed, seed, width, height,
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outputs=[result, seed]
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)
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+
model_name.change(change_base_model, [model_name], [result])
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gr.on(
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triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit],
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mod.py
CHANGED
@@ -73,14 +73,17 @@ base_model = models[0]
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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-
def change_base_model(repo_id: str):
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global pipe
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try:
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if not is_repo_name(repo_id) or not is_repo_exists(repo_id): return
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clear_cache()
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pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
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except Exception as e:
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print(e)
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def compose_lora_json(lorajson: list[dict], i: int, name: str, scale: float, filename: str, trigger: str):
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pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
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def change_base_model(repo_id: str, progress=gr.Progress(track_tqdm=True)):
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global pipe
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try:
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if not is_repo_name(repo_id) or not is_repo_exists(repo_id): return
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progress(0, f"Loading model: {repo_id}")
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clear_cache()
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pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
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progress(1, f"Model loaded: {repo_id}")
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except Exception as e:
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print(e)
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return gr.update(visible=True)
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def compose_lora_json(lorajson: list[dict], i: int, name: str, scale: float, filename: str, trigger: str):
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