alibaba / alibaba/EasyNLP

BeautifulPrompt released model (v2), questions about output prompt (optimized prompt)

Open
#367 1 comment 0 reactions 0 assignees View on GitHub
Dominant language
Python
Stars
2.2k
Forks
257
PR merge metrics
No merged PRs in 30d

Description

Thank you for your excellent work. I recently attempted to use the model you released on Hugging Face [https://huggingface.co/alibaba-pai/pai-bloom-1b1-text2prompt-sd-v2](url), but I encountered an issue with the output, as shown in the attached image.
image
My question is whether this type of optimized prompt can be directly input into Stable Diffusion in the source code, or is it exclusively for use in the web UI?
For example, the optimized prompt in the image is "(8k, RAW photo, best quality, masterpiece:1.2), (realistic, photo-realistic:1.37), octane render, ultra high res, photon mapping, radiosity, physically-based rendering, ue5, ((white dress)), ((long hair)), ((beautiful face)), ((light brown eyes)), ((smile))) extremely detailed CG unity 8k wallpaper, makeup, (glowing lips), (fantasy lining), (intricate details), light bokeh, (sharp focus) centered at the center of the face (wide angle:0.6), full body". It seems to exceed the maximum text length for Stable Diffusion XL. Can this type of optimized prompt be directly input into Stable Diffusion in the source code?

Contributor guide

No contributing guide indexed for this repository

Research direction

Start with the linked Hugging Face pai-bloom-1b-text2prompt-sd-v2 model and compare its generated prompt with Stable Diffusion XL's accepted input length. Confirm whether the optimized prompt can be passed through the source-code path or only the web UI, then document the supported usage and any length limitation.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface
Domain
ai, machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.