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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) |