Update app.py

app.py

@@ -1,38 +1,10 @@
 import spaces
 import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from transformers import BitsAndBytesConfig
+import torch
+import logging
+from diffusers import DiffusionPipeline
 
-quantization_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_compute_dtype=torch.bfloat16)
+pipe = DiffusionPipeline.from_pretrained("azaneko/HiDream-I1-Fast-nf4")
 
-model_name = "unsloth/Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-4bit"
-
-@spaces.GPU(duration=180)
-def load_model():
-    model = AutoModelForCausalLM.from_pretrained(model_name, quantization_config=quantization_config)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    return model, tokenizer
-
-@spaces.GPU
-def generate_text(prompt, model, tokenizer):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=100)
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-def gradio_interface():
-    model, tokenizer = load_model()
-    
-    def wrapped_generate(prompt):
-        return generate_text(prompt, model, tokenizer)
-    
-    iface = gr.Interface(
-        fn=wrapped_generate,
-        inputs="text",
-        outputs="text",
-        title="Meta-Llama 4 Scout 17B Instruct 4bit bnb"
-    )
-    return iface
-
-if __name__ == "__main__":
-    demo = gradio_interface()
-    demo.launch()
+prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
+image = pipe(prompt).images[0]