import gradio as gr import torch import random from transformers import T5Tokenizer, T5ForConditionalGeneration tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small") model = T5ForConditionalGeneration.from_pretrained("roborovski/superprompt-v1", torch_dtype=torch.float16) if torch.cuda.is_available(): device = "cuda" print("Using GPU") else: device = "cpu" print("Using CPU") model.to(device) def generate( system_prompt, prompt, max_new_tokens, repetition_penalty, temperature, top_p, top_k, random_seed, seed, ): input_text = f"{system_prompt}, {prompt}" input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(device) if random_seed: seed = random.randint(1, 100000) torch.manual_seed(seed) else: torch.manual_seed(seed) outputs = model.generate( input_ids, max_new_tokens=max_new_tokens, repetition_penalty=repetition_penalty, do_sample=True, temperature=temperature, top_p=top_p, top_k=top_k, ) better_prompt = tokenizer.decode(outputs[0]) return better_prompt prompt = gr.Textbox(label="Prompt", interactive=True) system_prompt = gr.Textbox(label="System Prompt", interactive=True) max_new_tokens = gr.Slider(value=512, minimum=250, maximum=512, step=1, interactive=True, label="Max New Tokens", info="The maximum numbers of new tokens, controls how long is the output") repetition_penalty = gr.Slider(value=1.2, minimum=0, maximum=2, step=0.05, interactive=True, label="Repetition Penalty", info="Penalize repeated tokens, making the AI repeat less itself") temperature = gr.Slider(value=0.5, minimum=0, maximum=1, step=0.05, interactive=True, label="Temperature", info="Higher values produce more diverse outputs") top_p = gr.Slider(value=1, minimum=0, maximum=2, step=0.05, interactive=True, label="Top P", info="Higher values sample more low-probability tokens") top_k = gr.Slider(value=1, minimum=1, maximum=100, step=1, interactive=True, label="Top K", info="Higher k means more diverse outputs by considering a range of tokens") use_random_seed = gr.Checkbox(value=False, label="Use Random Seed", info="Check to use a random seed which is a start point for the generation process") manual_seed = gr.Number(value=42, interactive=True, label="Manual Seed", info="A starting point to initiate the generation process", visible={'False' if use_random_seed else 'True'}) examples = [ [ "A storefront with 'Text to Image' written on it.", "Expand the following prompt to add more detail:", 512, 1.2, 0.5, 1, 50, False, 42, ] ] gr.Interface( fn=generate, inputs=[prompt, system_prompt, max_new_tokens, repetition_penalty, temperature, top_p, top_k, use_random_seed, manual_seed] outputs=gr.Textbox(label="Better Prompt", interactive=True) title="SuperPrompt-v1", description="Make your prompts more detailed!", examples=examples, live=True concurrency_limit=20, ).launch(show_api=False)