from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
device = "cuda" if torch.cuda.is_available() else "cpu"
# Model checkpoint
model_checkpoint = "gokaygokay/Flux-Prompt-Enhance"
# Tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
# Model
model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
enhancer = pipeline('text2text-generation',
model=model,
tokenizer=tokenizer,
repetition_penalty= 1.2,
device=device)
max_target_length = 256
prefix = "enhance prompt: "
short_prompt = "beautiful house with text 'hello'"
answer = enhancer(prefix + short_prompt, max_length=max_target_length)
final_answer = answer[0]['generated_text']
print(final_answer)
# a two-story house with white trim, large windows on the second floor,
# three chimneys on the roof, green trees and shrubs in front of the house,
# stone pathway leading to the front door, text on the house reads "hello" in all caps,
# blue sky above, shadows cast by the trees, sunlight creating contrast on the house's facade,
# some plants visible near the bottom right corner, overall warm and serene atmosphere.
Citation and attribution
This model release is maintained by Gökay Aydoğan. If you reference this repository in academic work, please cite it as follows and also cite the upstream models, datasets, or projects it builds upon.
@software{aydogan2024flux_prompt_enhance,
author = {Aydoğan, Gökay},
title = {{Flux-Prompt-Enhance}},
year = {2024},
publisher = {Hugging Face},
url = {https://huggingface.co/gokaygokay/Flux-Prompt-Enhance},
note = {Model repository; cite the base model and upstream datasets as required.}
}