Spaces:
				
			
			
	
			
			
					
		Running
		
	
	
	
			
			
	
	
	
	
		
		
					
		Running
		
	Update app.py
Browse files
    	
        app.py
    CHANGED
    
    | @@ -1,5 +1,6 @@ | |
| 1 | 
             
            import gradio as gr
         | 
| 2 | 
             
            import torch
         | 
|  | |
| 3 | 
             
            from transformers import T5Tokenizer, T5ForConditionalGeneration
         | 
| 4 |  | 
| 5 | 
             
            def load_model(model_path, dtype):
         | 
| @@ -42,6 +43,7 @@ def generate( | |
| 42 | 
             
                input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
         | 
| 43 |  | 
| 44 | 
             
                if seed_checkbox:
         | 
|  | |
| 45 | 
             
                    torch.manual_seed(seed)
         | 
| 46 |  | 
| 47 | 
             
                outputs = model.generate(
         | 
| @@ -107,6 +109,7 @@ additional_inputs = [ | |
| 107 | 
             
                    value=False,
         | 
| 108 | 
             
                    label="Use Random Seed",
         | 
| 109 | 
             
                    info="Check to use a random seed for the generation process",
         | 
|  | |
| 110 | 
             
                ),
         | 
| 111 | 
             
                gr.Number(
         | 
| 112 | 
             
                    value=42,
         | 
| @@ -122,6 +125,13 @@ additional_inputs = [ | |
| 122 | 
             
                ),
         | 
| 123 | 
             
            ]
         | 
| 124 |  | 
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
|  | |
| 125 | 
             
            examples = [
         | 
| 126 | 
             
                [
         | 
| 127 | 
             
                    "Expand the following prompt to add more detail: A storefront with 'Text to Image' written on it.",
         | 
|  | |
| 1 | 
             
            import gradio as gr
         | 
| 2 | 
             
            import torch
         | 
| 3 | 
            +
            import random
         | 
| 4 | 
             
            from transformers import T5Tokenizer, T5ForConditionalGeneration
         | 
| 5 |  | 
| 6 | 
             
            def load_model(model_path, dtype):
         | 
|  | |
| 43 | 
             
                input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device)
         | 
| 44 |  | 
| 45 | 
             
                if seed_checkbox:
         | 
| 46 | 
            +
                    seed = random.randint(1, 100000)
         | 
| 47 | 
             
                    torch.manual_seed(seed)
         | 
| 48 |  | 
| 49 | 
             
                outputs = model.generate(
         | 
|  | |
| 109 | 
             
                    value=False,
         | 
| 110 | 
             
                    label="Use Random Seed",
         | 
| 111 | 
             
                    info="Check to use a random seed for the generation process",
         | 
| 112 | 
            +
                    change=update_ui,
         | 
| 113 | 
             
                ),
         | 
| 114 | 
             
                gr.Number(
         | 
| 115 | 
             
                    value=42,
         | 
|  | |
| 125 | 
             
                ),
         | 
| 126 | 
             
            ]
         | 
| 127 |  | 
| 128 | 
            +
            def update_ui(seed_checkbox):
         | 
| 129 | 
            +
                if seed_checkbox:
         | 
| 130 | 
            +
                    return gr.Number.update(visible=False)
         | 
| 131 | 
            +
                else:
         | 
| 132 | 
            +
                    return gr.Number.update(visible=True)
         | 
| 133 | 
            +
             | 
| 134 | 
            +
             | 
| 135 | 
             
            examples = [
         | 
| 136 | 
             
                [
         | 
| 137 | 
             
                    "Expand the following prompt to add more detail: A storefront with 'Text to Image' written on it.",
         | 
 
			
