Create inference.py

inference.py

@@ -0,0 +1,14 @@
+from pathlib import Path
+from PIL import Image
+from transformers import AutoProcessor, AutoModel
+import torch
+
+# Load model and processor
+model = AutoModel.from_pretrained("cloudqi/cqi_text_to_image_pt_v0", trust_remote_code=True)
+processor = AutoProcessor.from_pretrained("cloudqi/cqi_text_to_image_pt_v0", trust_remote_code=True)
+
+def generate_image(prompt):
+    inputs = processor(prompt, return_tensors="pt")
+    with torch.no_grad():
+        output = model(**inputs).images[0]  # assumes .images exists
+    return Image.fromarray(output)