amirkhanbloch commited on
Commit
c4c5116
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1 Parent(s): d881e99

Update app.py

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Files changed (1) hide show
  1. app.py +13 -20
app.py CHANGED
@@ -2,24 +2,17 @@ import torch
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  import gradio as gr
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  from diffusers import StableDiffusion3Pipeline
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  import os
 
 
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- # Get the API token from environment variable (e.g., from Hugging Face Spaces Secrets)
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- api_token = os.getenv("HF_API_TOKEN")
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-
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- if not api_token:
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- raise ValueError("Hugging Face API token not found. Please set it in the Secrets.")
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-
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- # Set the environment variable for Hugging Face API token (if needed explicitly)
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- os.environ["HUGGING_FACE_HUB_TOKEN"] = api_token
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-
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  def image_generator(prompt):
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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- pipeline = StableDiffusion3Pipeline.from_pretrained(
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- "stabilityai/stable-diffusion-3-medium-diffusers",
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- torch_dtype=torch.float16 if device == "cuda" else torch.float32,
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- text_encoder_3=None,
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- tokenizer_3=None
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- )
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  pipeline.to(device)
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  image = pipeline(
@@ -35,9 +28,9 @@ def image_generator(prompt):
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  interface = gr.Interface(
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  fn=image_generator,
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- inputs=gr.Textbox(lines=2, placeholder="Enter your prompt..."),
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- outputs=gr.Image(type="pil"),
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- title="Image Generator App",
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- description="This is a simple image generator app using HuggingFace's Stable Diffusion 3 model."
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- )
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  interface.launch()
 
 
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  import gradio as gr
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  from diffusers import StableDiffusion3Pipeline
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  import os
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+ from huggingface_hub import login
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+ hf_token = os.getenv("HF_API_TOKEN")
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+ login(token=hf_token)
 
 
 
 
 
 
 
 
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  def image_generator(prompt):
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  device = "cuda" if torch.cuda.is_available() else "cpu"
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+ pipeline = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers",
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+ torch_dtype=torch.float16 if device == "cuda" else torch.float32,
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+ text_encoder_3=None,
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+ tokenizer_3 = None)
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+ #pipeline.enable_model_cpu_offload()
 
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  pipeline.to(device)
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  image = pipeline(
 
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  interface = gr.Interface(
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  fn=image_generator,
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+ inputs=gr.Textbox(lines=2, placeholder = "Enter your prompt..."),
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+ outputs=gr.Image(type = "pil"),
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+ title = "Image Generator App",
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+ description = "This is a simple image generator app using HuggingFace's Stable Diffusion 3 model.")
 
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  interface.launch()
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+ print(interface)