license: openrail++
pipeline_tag: text-to-image
tags:
- stable-diffusion
- text-to-image
- diffusers
- DiffusionPipeline
inference:
parameter:
negative_prompt: >-
lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit,
fewer digits, cropped, worst quality, low quality, normal quality, jpeg,
artifacts, signature, watermark, username, blurry, ugly, duplicate,
morbid, mutilated, extra fingers, mutated hands, poorly drawn hands,
poorly drawn face, mutation, deformed, blurry, bad anatomy, bad
proportions, cloned face, disfigured, out of frame, extra limbs, bad
anatomy, gross proportions, malformed limbs, missing arms, missing legs,
extra arms, extra legs, mutated hands, fused fingers, too many fingers,
long neck, text, letters, signature, web address, copyright name,
username, error, extra digit, fewer digits, loadscreen, grid, stock image,
a stock photo, promo poster, fat, text, logo, brand, watermark, water
mark, low quality,
widget:
- text: melaura, girl, hd, pink lips, detailed, age 16, Off-shoulder top
example_title: Off-shoulder top
- text: melaura, girl, hd, shiny cheeks
example_title: shiny cheeks
library_name: diffusers
For best results, use the following command
- prompt (Trigger Words):
melaura, girl
- negative prompts:
ugly, duplicate, morbid, mutilated, extra fingers, mutated hands, poorly drawn hands, poorly drawn face, mutation, deformed, blurry, bad anatomy, bad proportions, cloned face, disfigured, out of frame, extra limbs, bad anatomy, gross proportions, malformed limbs, missing arms, missing legs, extra arms, extra legs, mutated hands, fused fingers, too many fingers, long neck, text, letters, signature, web address, copyright name, username, error, extra digit, fewer digits, loadscreen, grid, stock image, a stock photo, promo poster, fat, text, logo, brand, watermark, water mark, low quality,
- scheduler: EulerAncestralDiscreteScheduler (Euler a).
License: CreativeML Open RAIL++-M License
You are free to:
- Share - copy and redistribute the material in any medium or format
- Adapt - remix, transform, and build upon the material
Under the following terms:
- Attribution - You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial - You may not use the material for commercial purposes.
Examples of prompts used
Prompt: melaura, girl, asian woman with long dark hair wearing a white dress, a photorealistic painting by Lü Ji, trending on cg society, photorealism, popular korean makeup, popular south korean makeup, clear makeup
Guidance_Scale: 7.5
Num_Inference_Steps: 50
scheduler type: EulerAncestralDiscreteScheduler
Prompt: melaura, girl, a woman with a pearl necklace and pearl necklace, a photorealistic painting by Kim Deuk-sin, featured on cg society, photorealism, portrait of female korean idol, popular korean makeup, popular south korean makeup, shiny cheeks
Guidance_Scale: 7.5
Num_Inference_Steps: 50
scheduler type: EulerAncestralDiscreteScheduler
Prompt: melaura, girl,
Guidance_Scale: 7.5
Num_Inference_Steps: 50
scheduler type: EulerAncestralDiscreteScheduler
Gradio & Colab
We also support a Gradio Web UI and Colab with Diffusers to run Melaura:
🧨 Diffusers
Before running it, make sure you have the necessary pip libraries installed:
pip install -q diffusers transformers omegaconf
Running the pipeline (if you don't swap the scheduler, it will run with the default EulerDiscreteScheduler. In this example, we're swapping it to EulerAncestralDiscreteScheduler:
from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler
import torch
import os
repo_id = "DamarJati/melaura-v1"
pipe = StableDiffusionPipeline.from_pretrained(
repo_id,
torch_dtype=torch.float16,
use_karras_sigmas=True,
algorithm_type="sde-dpmsolver++"
)
pipe.to('cuda')
#Safety Checker
pipe.safety_checker = None
pipe.requires_safety_checker = False
#Scheduler
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
Prompt = "melaura, girl, hd, pink lips, detailed, age 16, Off-shoulder top, shiny cheeks"
Negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"
image = pipe(
prompt=Prompt,
negative_prompt=Negative_prompt,
width=512,
height=512,
guidance_scale=8,
num_inference_steps=50
).images[0]
image.save("melaura.png")
Limitation
This model inherit Stable Diffusion 1.5 limitation