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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
import gradio as gr | |
tokenizer = AutoTokenizer.from_pretrained("merve/chatgpt-prompts-bart-long") | |
model = AutoModelForSeq2SeqLM.from_pretrained("merve/chatgpt-prompts-bart-long", from_tf=True) | |
def generate(prompt): | |
batch = tokenizer(prompt, return_tensors="pt") | |
generated_ids = model.generate(batch["input_ids"], max_new_tokens=150) | |
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) | |
return output[0] | |
input_component = gr.Textbox(label = "Input a persona, e.g. photographer", value = "photographer") | |
output_component = gr.Textbox(label = "Prompt") | |
examples = [] | |
description = "" | |
gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "ChatGPT Prompt Generator", description=description).launch() | |