metadata

license: creativeml-openrail-m
base_model: segmind/SSD-1B
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
  - full
inference: true

terminus-lite-base-v1

This is a full rank finetune derived from segmind/SSD-1B.

The main validation prompt used during training was:

a cute anime character named toast

Validation settings

CFG: 7.5
CFG Rescale: 0.7
Steps: 30
Sampler: euler
Seed: 420420420
Resolutions: 1024x1024,1152x960,896x1152

Note: The validation settings are not necessarily the same as the training settings.

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

Training settings

Training epochs: 0
Training steps: 600
Learning rate: 1e-06
Effective batch size: 16
- Micro-batch size: 4
- Gradient accumulation steps: 4
- Number of GPUs: 1
Prediction type: v_prediction
Rescaled betas zero SNR: True
Optimizer: AdamW, stochastic bf16
Precision: Pure BF16
Xformers: Not used

Datasets

celebrities

Repeats: 4
Total number of images: 1232
Total number of aspect buckets: 2
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

movieposters

Repeats: 25
Total number of images: 1712
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

normalnudes

Repeats: 5
Total number of images: 1120
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

propagandaposters

Repeats: 0
Total number of images: 560
Total number of aspect buckets: 2
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

guys

Repeats: 5
Total number of images: 368
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

pixel-art

Repeats: 0
Total number of images: 1040
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

signs

Repeats: 25
Total number of images: 384
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

moviecollection

Repeats: 0
Total number of images: 1888
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

bookcovers

Repeats: 0
Total number of images: 800
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

nijijourney

Repeats: 0
Total number of images: 560
Total number of aspect buckets: 1
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

experimental

Repeats: 0
Total number of images: 3024
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

ethnic

Repeats: 0
Total number of images: 3072
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

sports

Repeats: 0
Total number of images: 784
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

gay

Repeats: 0
Total number of images: 1072
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

architecture

Repeats: 0
Total number of images: 4336
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

shutterstock

Repeats: 0
Total number of images: 21088
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

cinemamix-1mp

Repeats: 0
Total number of images: 9008
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

nsfw-1024

Repeats: 0
Total number of images: 10800
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

anatomy

Repeats: 5
Total number of images: 16400
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

bg20k-1024

Repeats: 0
Total number of images: 89280
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

yoga

Repeats: 0
Total number of images: 3600
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

photo-aesthetics

Repeats: 0
Total number of images: 33120
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

text-1mp

Repeats: 25
Total number of images: 13168
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

photo-concept-bucket

Repeats: 0
Total number of images: 567536
Total number of aspect buckets: 3
Resolution: 1.0 megapixels
Cropped: True
Crop style: random
Crop aspect: random

Inference

import torch
from diffusers import DiffusionPipeline



model_id = "terminus-lite-base-v1"
prompt = "a cute anime character named toast"
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=0.7,
).images[0]
image.save("output.png", format="PNG")