NeuroPrompts: An Adaptive Framework to Optimize Prompts for Text-to-Image Generation
Paper • 2311.12229 • Published • 25
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Intel/NeuroPrompts")
model = AutoModelForCausalLM.from_pretrained("Intel/NeuroPrompts")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
NeuroPrompts Model Card
NeuroPrompts is an interface to Stable Diffusion which automatically optimizes a user’s prompt for improved image aesthetics while maintaining stylistic control according to the user’s preferences. Preprint: arxiv.org/abs/2311.12229
NeuroPrompts was accepted to EACL 2024.
The interface of NeuroPrompts in side-by-side comparison mode
Usage
This model is inteded to be used within the NeuroPrompts application.
Please see our GitHub repository for instructions on how to run NeuroPrompts: https://github.com/IntelLabs/multimodal_cognitive_ai/tree/main/Demos/NeuroPrompts
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Intel/NeuroPrompts")