Update app.py

app.py

@@ -1,27 +1,4 @@
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-from PIL import Image
-import base64
-import io
+from huggingface_hub import snapshot_download
 
-# Load model and tokenizer
-model = AutoModelForCausalLM.from_pretrained("cloudqi/cqi_text_to_image_pt_v0")
-tokenizer = AutoTokenizer.from_pretrained("cloudqi/cqi_text_to_image_pt_v0")
-
-def generate_image(prompt):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    output_ids = model.generate(**inputs, max_length=256)
-    output_str = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-
-    # Decode base64 to image
-    if "data:image/png;base64," in output_str:
-        b64_img = output_str.split("data:image/png;base64,")[1]
-        image_data = base64.b64decode(b64_img)
-        image = Image.open(io.BytesIO(image_data))
-        return image
-    return "No image found in output."
-
-demo = gr.Interface(fn=generate_image, inputs="text", outputs="image", title="CQI Text-to-Image")
-
-demo.launch()
+local_dir = snapshot_download(repo_id="cloudqi/cqi_text_to_image_pt_v0")
+print(f"Model files downloaded to: {local_dir}")