metadata
license: creativeml-openrail-m
base_model: PixArt-alpha/PixArt-Sigma-XL-2-1024-MS
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- full
inference: true
widget:
- text: >-
A blonde sexy girl, wearing glasses at latex shirt and a blue beanie with
a tattoo, blue and white, highly detailed, sublime, extremely beautiful,
sharp focus, refined, cinematic, intricate, elegant, dynamic, rich deep
colors, bright color, shining light, attractive, cute, pretty, background
full, epic composition, dramatic atmosphere, radiant, professional,
stunning
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/1.png
- text: >-
a wizard with a glowing staff and a glowing hat, colorful magic, dramatic
atmosphere, sharp focus, highly detailed, cinematic, original composition,
fine detail, intricate, elegant, creative, color spread, shiny, amazing,
symmetry, illuminated, inspired, pretty, attractive, artistic, dynamic
background, relaxed, professional, extremely inspirational, beautiful,
determined, cute, adorable, best
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/2.png
- text: >-
girl in modern car, intricate, elegant, highly detailed, extremely
complimentary colors, beautiful, glowing aesthetic, pretty, dramatic
light, sharp focus, perfect composition, clear artistic color, calm
professional background, precise, joyful, emotional, unique, cute, best,
gorgeous, great delicate, expressive, thought, iconic, fine, awesome,
creative, winning, charming, enhanced
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/3.png
- text: >-
girl in modern car, intricate, elegant, highly detailed, extremely
complimentary colors, beautiful, glowing aesthetic, pretty, dramatic
light, sharp focus, perfect composition, clear artistic color, calm
professional background, precise, joyful, emotional, unique, cute, best,
gorgeous, great delicate, expressive, thought, iconic, fine, awesome,
creative, winning, charming, enhanced
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/3.png
- text: >-
A girl stands amidst scattered glass shards, surrounded by a beautifully
crafted and expansive world. The scene is depicted from a dynamic angle,
emphasizing her determined expression. The background features vast
landscapes with floating crystals and soft, glowing lights that create a
mystical and grand atmosphere.
parameters:
negative_prompt: blurry, cropped, ugly
output:
url: ./assets/ComfyUI_PixArt_00036_.png
pixart-training
This is a full rank finetune derived from PixArt-alpha/PixArt-Sigma-XL-2-1024-MS.
No validation prompt was used during training.
None
Validation settings
- CFG:
7.5
- CFG Rescale:
0.0
- Steps:
30
- Sampler:
euler
- Seed:
42
- Resolution:
1024
Note: The validation settings are not necessarily the same as the training settings.
You can find some example images in the following gallery:
The text encoder was not trained. You may reuse the base model text encoder for inference.
Training settings
- Training epochs: 5
- Training steps: 6500
- Learning rate: 8e-06
- Effective batch size: 128
- Micro-batch size: 32
- Gradient accumulation steps: 4
- Number of GPUs: 1
- Prediction type: epsilon
- Rescaled betas zero SNR: False
- Optimizer: AdamW, stochastic bf16
- Precision: Pure BF16
- Xformers: Enabled
Datasets
mj-v6
- Repeats: 0
- Total number of images: 134144
- Total number of aspect buckets: 1
- Resolution: 1.0 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
Inference
import torch
from diffusers import DiffusionPipeline
model_id = "pixart-training"
prompt = "An astronaut is riding a horse through the jungles of Thailand."
negative_prompt = "malformed, disgusting, overexposed, washed-out"
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
image = pipeline(
prompt=prompt,
negative_prompt='blurry, cropped, ugly',
num_inference_steps=30,
generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
width=1152,
height=768,
guidance_scale=7.5,
guidance_rescale=0.0,
).images[0]
image.save("output.png", format="PNG")