Create app.py

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+   import torch
+   from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+   MODEL_NAME = "cloudqi/cqi_text_to_image_pt_v0"
+   tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+   model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+
+   def generate_images(description):
+       input_ids = tokenizer.encode(description, return_tensors="pt")
+       # Model generates a batch of one image
+       output = model.generate(input_ids)
+       output_image = output[0].numpy().transpose(1,2,0)
+       return output_image.astype("uint8")
+
+   inputs = gr.inputs.Textbox(prompt="Enter Text Description")
+   outputs = gr.outputs.Image(label="Generated Image")
+
+   iface = gr.Interface(fn=generate_images, inputs=inputs, outputs=outputs, title="Description to Image")
+   iface.disable_caching=True  # Disable caching to ensure the model is reloaded each time the app is opened
+
+   if __name__ == "__main__":
+       iface.launch()