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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 = [["photographer"], ["developer"]] | |
# Beschreibung hier korrekt eingerückt | |
description = "Wunsch Rolle eingeben und Enter klicken - Kaffee oder Tee holen und Einfach.Prompt kopieren und einsetzen [this dataset](https://huggingface.co/datasets/fka/awesome-chatgpt-prompts). " | |
gr.Interface( | |
generate, | |
inputs=input_component, | |
outputs=output_component, | |
examples=examples, | |
title="👨🏻🎤 ChatGPT Prompt Generator 👨🏻🎤", | |
description=description, | |
theme="ParityError/Interstellar" # Hinzugefügtes Theme | |
).launch() | |