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alfredplpl
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Parent(s):
114766c
Update app.py
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app.py
CHANGED
@@ -5,16 +5,25 @@ import spaces
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import torch
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import os
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model_id = "aipicasso/emi-2"
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token=os.environ["TOKEN"]
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scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id,subfolder="scheduler",token=token)
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pipe_normal = StableDiffusionXLPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.bfloat16,token=token)
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pipe_normal.to("cuda")
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@spaces.GPU
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def run_normal(prompt, negative_prompt="", guidance_scale=7, progress=gr.Progress(track_tqdm=True)):
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return pipe_normal(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, num_inference_steps=20).images[0]
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css = '''
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.gradio-container{
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@@ -23,14 +32,14 @@ margin: 0 auto;
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}
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'''
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normal_examples = ["
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with gr.Blocks(css=css) as demo:
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gr.Markdown('''# Emi 2
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Official demo for Emi 2
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''')
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with gr.Group():
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with gr.Row():
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prompt_normal = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt, e.g.:
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button_normal = gr.Button("Generate", min_width=120)
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output_normal = gr.Image(label="Your result image", interactive=False)
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with gr.Accordion("Advanced Settings", open=False):
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import torch
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import os
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from huggingface_hub import hf_hub_download
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model_id = "aipicasso/emi-2"
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token=os.environ["TOKEN"]
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scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id,subfolder="scheduler",token=token)
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pipe_normal = StableDiffusionXLPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.bfloat16,token=token)
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negative_ti_file = hf_hub_download(repo_id="Aikimi/unaestheticXL_Negative_TI", filename="unaestheticXLv31.safetensors")
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state_dict = load_file(negative_ti_file)
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pipe.load_textual_inversion(state_dict["clip_g"], token="unaestheticXLv31", text_encoder=pipe.text_encoder_2, tokenizer=pipe.tokenizer_2)
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pipe.load_textual_inversion(state_dict["clip_l"], token="unaestheticXLv31", text_encoder=pipe.text_encoder, tokenizer=pipe.tokenizer)
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pipe_normal.to("cuda")
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@spaces.GPU
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def run_normal(prompt, negative_prompt="", guidance_scale=7.5, progress=gr.Progress(track_tqdm=True)):
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return pipe_normal(prompt, negative_prompt="unaestheticXLv31"+negative_prompt, guidance_scale=guidance_scale, num_inference_steps=20).images[0]
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css = '''
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.gradio-container{
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}
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'''
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normal_examples = ["1girl, face, brown bob short hair, brown eyes, looking at viewer"]
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with gr.Blocks(css=css) as demo:
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gr.Markdown('''# Emi 2
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Official demo for Emi 2
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''')
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with gr.Group():
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with gr.Row():
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prompt_normal = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt, e.g.: 1girl, face, brown bob short hair, brown eyes, looking at viewer")
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button_normal = gr.Button("Generate", min_width=120)
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output_normal = gr.Image(label="Your result image", interactive=False)
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with gr.Accordion("Advanced Settings", open=False):
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