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: unconditional (blank prompt)
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_0_0.png
  - text: ethnographic photography of teddy bear at a picnic
    parameters:
      negative_prompt: blurry, cropped, ugly
    output:
      url: ./assets/image_1_0.png

pixart-training

This is a full rank finetune derived from PixArt-alpha/PixArt-Sigma-XL-2-1024-MS.

The main validation prompt used during training was:

ethnographic photography of teddy bear at a picnic

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:

Prompt
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

Negative Prompt
blurry, cropped, ugly

Prompt
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

Negative Prompt
blurry, cropped, ugly

Prompt
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

Negative Prompt
blurry, cropped, ugly

Prompt
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.

Negative Prompt
blurry, cropped, ugly

Prompt
A close-up shot of a beautiful girl in a serene world. She has white hair and is blindfolded, with a calm expression. Her hands are pressed together in a prayer pose, with fingers interlaced and palms touching. The background is softly blurred, enhancing her ethereal presence.

Negative Prompt
blurry, cropped, ugly

The text encoder was not trained. You may reuse the base model text encoder for inference.

Training settings

Training epochs: 0
Training steps: 1000
Learning rate: 8e-06
Effective batch size: 96
- Micro-batch size: 32
- Gradient accumulation steps: 3
- 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: 199872
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 = "ethnographic photography of teddy bear at a picnic"
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")