Flux Prompt Enhancer

🚀 Flux Prompt Enhancer

A model fine-tuned to convert short prompts into detailed ones for high - quality image generation using stable diffusion or flux.

🚀 Quick Start

Use the following code to start using the model:

from transformers import T5Tokenizer, T5ForConditionalGeneration

# Load the tokenizer and model
tokenizer = T5Tokenizer.from_pretrained("imranali291/flux-prompt-enhancer")
model = T5ForConditionalGeneration.from_pretrained("imranali291/flux-prompt-enhancer")

# Example input
input_text = "Futuristic cityscape at twilight descent."

# Tokenize input
input_ids = tokenizer(input_text, return_tensors="pt").input_ids

# Generate output
output = model.generate(input_ids, max_length=128, eos_token_id=tokenizer.eos_token_id, do_sample=True, top_p=0.9, temperature=0.7, repetition_penalty=2.5)
print(tokenizer.decode(output[0], skip_special_tokens=True))

✨ Features

The model has been fine - tuned to optimize the conversion of short prompts into detailed prompts. This allows for stable diffusion or flux - based image generation, enabling users to create more specific and nuanced requests, which results in higher - quality and more coherent images.

📚 Documentation

Model Description

📄 License

This model is licensed under the apache - 2.0 license.