README.md

---
license: creativeml-openrail-m
base_model: "ptx0/pixart-900m-1024-ft-large"
tags:
  - stable-diffusion
  - stable-diffusion-diffusers
  - text-to-image
  - diffusers
  - simpletuner
  - full

inference: true

---

# pixart-900m-1024-ft

This is a full rank finetune derived from [ptx0/pixart-900m-1024-ft-large](https://huggingface.co/ptx0/pixart-900m-1024-ft-large).



The main validation prompt used during training was:

```
ethnographic photography of teddy bear at a picnic, ears tucked behind a cozy hoodie looking darkly off to the stormy picnic skies
```

## Validation settings
- CFG: `4.5`
- CFG Rescale: `0.0`
- Steps: `25`
- Sampler: `None`
- Seed: `42`
- Resolutions: `1024x1024,1344x768,916x1152`

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: 1
- Training steps: 49000
- Learning rate: 1e-06
- Effective batch size: 192
  - Micro-batch size: 24
  - Gradient accumulation steps: 1
  - Number of GPUs: 8
- Prediction type: epsilon
- Rescaled betas zero SNR: False
- Optimizer: AdamW, stochastic bf16
- Precision: Pure BF16
- Xformers: Not used


## Datasets

### photo-concept-bucket
- Repeats: 0
- Total number of images: ~567360
- Total number of aspect buckets: 4
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: random
### midjourney-v6-520k-raw
- Repeats: 0
- Total number of images: ~390912
- Total number of aspect buckets: 1
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### sfwbooru
- Repeats: 0
- Total number of images: ~233664
- Total number of aspect buckets: 1
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### nijijourney-v6-520k-raw
- Repeats: 0
- Total number of images: ~416064
- Total number of aspect buckets: 1
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square
### dalle3
- Repeats: 0
- Total number of images: ~1889680
- Total number of aspect buckets: 1
- Resolution: 1.0 megapixels
- Cropped: True
- Crop style: random
- Crop aspect: square


## Inference


```python
import torch
from diffusers import DiffusionPipeline




model_id = 'pixart-900m-1024-ft'
prompt = 'ethnographic photography of teddy bear at a picnic, ears tucked behind a cozy hoodie looking darkly off to the stormy picnic skies'
negative_prompt = 'blurry, cropped, ugly'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')

prompt = "ethnographic photography of teddy bear at a picnic, ears tucked behind a cozy hoodie looking darkly off to the stormy picnic skies"
negative_prompt = "blurry, cropped, ugly"

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=25,
    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=4.5,
    guidance_rescale=0.0,
).images[0]
image.save("output.png", format="PNG")
```