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

inference: true

---

# terminus-xl-refiner

This is a full rank finetune derived from [segmind/SSD-1B](https://huggingface.co/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](#training-settings).




<Gallery />

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


```python
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")
```