terminus-xl-refiner
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:
ddpm - Seed:
420420420 - Resolution:
1024
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: 12800
- Learning rate: 2e-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: Enabled
Datasets
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: 0
- Total number of images: 368
- Total number of aspect buckets: 3
- 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
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: 21072
- 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: 16417
- 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: 33136
- Total number of aspect buckets: 3
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: random
text-1mp
- Repeats: 5
- Total number of images: 13170
- 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: 567554
- 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-xl-refiner"
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")
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Model tree for bghira/terminus-xl-refiner
Base model
segmind/SSD-1B