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e9d3b6c 67ad199 234157e e9d3b6c 234157e e9d3b6c 67ad199 234157e e9d3b6c 234157e 67ad199 e9d3b6c 234157e e9d3b6c 234157e 67ad199 234157e e9d3b6c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | import gradio as gr
import torch
import os
import spaces
from diffusers import FluxPipeline
# मॉडल आईडी
model_id = "black-forest-labs/FLUX.1-dev"
# Gated मॉडल के लिए टोकन और ऑथेंटिकेशन
hf_token = os.environ.get("HF_TOKEN")
# पाइपलाइन लोड करें (token पैरामीटर का उपयोग करके)
pipe = FluxPipeline.from_pretrained(
model_id,
token=hf_token,
torch_dtype=torch.bfloat16
)
pipe = pipe.to("cuda")
@spaces.GPU
def generate_image(prompt):
# ZeroGPU के लिए जरूरी @spaces.GPU डेकोरेटर
image = pipe(
prompt,
height=768,
width=1024,
guidance_scale=3.5,
num_inference_steps=20,
max_sequence_length=512,
).images[0]
return image
# Gradio इंटरफेस
demo = gr.Interface(
fn=generate_image,
inputs=gr.Textbox(label="Prompt", placeholder="Describe your realistic image..."),
outputs=gr.Image(label="Generated Image"),
title="Flux.1 Dev - Gated Model"
)
if __name__ == "__main__":
demo.launch()
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