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Running
on
Zero
Running
on
Zero
Update app-backup.py
Browse files- app-backup.py +21 -28
app-backup.py
CHANGED
@@ -24,6 +24,9 @@ from transformers import T5EncoderModel, T5Tokenizer
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# from optimum.quanto import freeze, qfloat8, quantize
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from transformers import pipeline
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class HFEmbedder(nn.Module):
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def __init__(self, version: str, max_length: int, **hf_kwargs):
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super().__init__()
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@@ -746,12 +749,8 @@ model = Flux().to(dtype=torch.bfloat16, device="cuda")
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result = model.load_state_dict(sd)
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model_zero_init = False
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ko_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
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ja_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ja-en")
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zh_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-zh-en")
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@spaces.GPU
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@@ -763,17 +762,14 @@ def generate_image(
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):
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translated_prompt = prompt
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#
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def contains_korean(text):
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return any('\u3131' <= c <= '\u318E' or '\uAC00' <= c <= '\uD7A3' for c in text)
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def contains_japanese(text):
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return any('\u3040' <= c <= '\u309F' or '\u30A0' <= c <= '\u30FF' or '\u4E00' <= c <= '\u9FFF' for c in text)
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return any('\u4e00' <= c <= '\u9fff' for c in text)
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# ํ๊ธ, ์ผ๋ณธ์ด, ์ค๊ตญ์ด๊ฐ ์์ผ๋ฉด ๋ฒ์ญ
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if contains_korean(prompt):
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translated_prompt = ko_translator(prompt, max_length=512)[0]['translation_text']
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print(f"Translated Korean prompt: {translated_prompt}")
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@@ -782,14 +778,6 @@ def generate_image(
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translated_prompt = ja_translator(prompt, max_length=512)[0]['translation_text']
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print(f"Translated Japanese prompt: {translated_prompt}")
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prompt = translated_prompt
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elif contains_chinese(prompt):
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translated_prompt = zh_translator(prompt, max_length=512)[0]['translation_text']
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print(f"Translated Chinese prompt: {translated_prompt}")
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prompt = translated_prompt
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if seed == 0:
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seed = int(random.random() * 1000000)
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@@ -855,10 +843,10 @@ footer {
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def create_demo():
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with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css) as demo:
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt(
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width = gr.Slider(minimum=128, maximum=2048, step=64, label="Width", value=768)
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height = gr.Slider(minimum=128, maximum=2048, step=64, label="Height", value=768)
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@@ -880,6 +868,17 @@ def create_demo():
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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output_seed = gr.Text(label="Used Seed")
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do_img2img.change(
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fn=lambda x: [gr.update(visible=x), gr.update(visible=x), gr.update(visible=x)],
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generate_button.click(
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fn=generate_image,
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inputs=[prompt, width, height, guidance, inference_steps, seed, do_img2img, init_image, image2image_strength, resize_img],
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outputs=[output_image, output_seed]
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)
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examples = [
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"a tiny astronaut hatching from an egg on the moon",
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"a cat holding a sign that says hello world",
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"an anime illustration of a wiener schnitzel",
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]
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return demo
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# from optimum.quanto import freeze, qfloat8, quantize
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from transformers import pipeline
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ko_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
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ja_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ja-en")
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class HFEmbedder(nn.Module):
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def __init__(self, version: str, max_length: int, **hf_kwargs):
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super().__init__()
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result = model.load_state_dict(sd)
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model_zero_init = False
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# model = Flux().to(dtype=torch.bfloat16, device="cuda")
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# result = model.load_state_dict(load_file("/storage/dev/nyanko/flux-dev/flux1-dev.sft"))
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@spaces.GPU
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):
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translated_prompt = prompt
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# ํ๊ธ ๋๋ ์ผ๋ณธ์ด ๋ฌธ์ ๊ฐ์ง
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def contains_korean(text):
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return any('\u3131' <= c <= '\u318E' or '\uAC00' <= c <= '\uD7A3' for c in text)
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def contains_japanese(text):
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return any('\u3040' <= c <= '\u309F' or '\u30A0' <= c <= '\u30FF' or '\u4E00' <= c <= '\u9FFF' for c in text)
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# ํ๊ธ์ด๋ ์ผ๋ณธ์ด๊ฐ ์์ผ๋ฉด ๋ฒ์ญ
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if contains_korean(prompt):
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translated_prompt = ko_translator(prompt, max_length=512)[0]['translation_text']
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print(f"Translated Korean prompt: {translated_prompt}")
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translated_prompt = ja_translator(prompt, max_length=512)[0]['translation_text']
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print(f"Translated Japanese prompt: {translated_prompt}")
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prompt = translated_prompt
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if seed == 0:
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seed = int(random.random() * 1000000)
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def create_demo():
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with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css) as demo:
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gr.Markdown("# FLUXllama Multilingual")
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with gr.Row():
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with gr.Column():
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prompt = gr.Textbox(label="Prompt(Supports English, Korean, and Japanese)", value="A cute and fluffy golden retriever puppy sitting upright, holding a neatly designed white sign with bold, colorful lettering that reads 'Have a Happy Day!' in cheerful fonts. The puppy has expressive, sparkling eyes, a happy smile, and fluffy ears slightly flopped. The background is a vibrant and sunny meadow with soft-focus flowers, glowing sunlight filtering through the trees, and a warm golden glow that enhances the joyful atmosphere. The sign is framed with small decorative flowers, adding a charming and wholesome touch. Ensure the text on the sign is clear and legible.")
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width = gr.Slider(minimum=128, maximum=2048, step=64, label="Width", value=768)
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height = gr.Slider(minimum=128, maximum=2048, step=64, label="Height", value=768)
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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output_seed = gr.Text(label="Used Seed")
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output_translated = gr.Text(label="Translated Prompt")
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# Examples ์ปดํฌ๋ํธ ์ถ๊ฐ
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gr.Examples(
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examples=[
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"a tiny astronaut hatching from an egg on the moon",
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"์ฌ๊ธ๋ผ์ค ์ฐฉ์ฉํ ๊ท์ฌ์ด ํฐ์ ๊ณ ์์ด๊ฐ 'LOVE'๋ผ๋ ํ์งํ์ ๋ค๊ณ ์๋ค",
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"ๆกใๆตใใๅคใฎ่กใ็
งๆ",
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],
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inputs=prompt, # ์์ ๊ฐ ์
๋ ฅ๋ ์ปดํฌ๋ํธ ์ง์
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)
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do_img2img.change(
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fn=lambda x: [gr.update(visible=x), gr.update(visible=x), gr.update(visible=x)],
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generate_button.click(
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fn=generate_image,
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inputs=[prompt, width, height, guidance, inference_steps, seed, do_img2img, init_image, image2image_strength, resize_img],
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outputs=[output_image, output_seed, output_translated]
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)
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return demo
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