---
license: other
base_model: "terminusresearch/sana-1.6b-1024px"
tags:
  - sana
  - sana-diffusers
  - text-to-image
  - diffusers
  - simpletuner
  - not-for-all-audiences
  - lora
  - template:sd-lora
  - lycoris
inference: true
widget:
- text: 'unconditional (blank prompt)'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_0_0.png
- text: 'unconditional (blank prompt)'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_1_1.png
- text: 'A photo of mikrei eating a delicious slice of pizza at a restaurant'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_2_0.png
- text: 'A photo of mikrei eating a delicious slice of pizza at a restaurant'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_3_1.png
- text: 'A photo of mikrei feeding a dinousaur in a jungle with lush vegetation and cinematic lighting'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_4_0.png
- text: 'A photo of mikrei feeding a dinousaur in a jungle with lush vegetation and cinematic lighting'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_5_1.png
- text: 'professional portrait of serious mikrei in a cockpit with instruments piloting a luxurious private jet in dramatic weather'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_6_0.png
- text: 'professional portrait of serious mikrei in a cockpit with instruments piloting a luxurious private jet in dramatic weather'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_7_1.png
- text: 'close-up portrait of mikrei on a throne in a magnificent palace wearing a crown and royal attire'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_8_0.png
- text: 'close-up portrait of mikrei on a throne in a magnificent palace wearing a crown and royal attire'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_9_1.png
- text: 'a high-quality, detailed photograph of mikrei as a sous-chef, immersed in the art of culinary creation'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_10_0.png
- text: 'a high-quality, detailed photograph of mikrei as a sous-chef, immersed in the art of culinary creation'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_11_1.png
- text: 'a lifelike and intimate portrait of mikrei, showcasing his unique personality and charm'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_12_0.png
- text: 'a lifelike and intimate portrait of mikrei, showcasing his unique personality and charm'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_13_1.png
- text: 'a cinematic, visually stunning photo of mikrei, emphasizing his dramatic and captivating presence'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_14_0.png
- text: 'a cinematic, visually stunning photo of mikrei, emphasizing his dramatic and captivating presence'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_15_1.png
- text: 'an elegant and timeless portrait of mikrei, exuding grace and sophistication'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_16_0.png
- text: 'an elegant and timeless portrait of mikrei, exuding grace and sophistication'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_17_1.png
- text: 'a dynamic and adventurous photo of mikrei, captured in an exciting, action-filled moment'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_18_0.png
- text: 'a dynamic and adventurous photo of mikrei, captured in an exciting, action-filled moment'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_19_1.png
- text: 'a mysterious and enigmatic portrait of mikrei, shrouded in shadows and intrigue'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_20_0.png
- text: 'a mysterious and enigmatic portrait of mikrei, shrouded in shadows and intrigue'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_21_1.png
- text: 'a vintage-style portrait of mikrei, evoking the charm and nostalgia of a bygone era'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_22_0.png
- text: 'a vintage-style portrait of mikrei, evoking the charm and nostalgia of a bygone era'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_23_1.png
- text: 'an artistic and abstract representation of mikrei, blending creativity with visual storytelling'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_24_0.png
- text: 'an artistic and abstract representation of mikrei, blending creativity with visual storytelling'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_25_1.png
- text: 'a futuristic and cutting-edge portrayal of mikrei, set against a backdrop of advanced technology'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_26_0.png
- text: 'a futuristic and cutting-edge portrayal of mikrei, set against a backdrop of advanced technology'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_27_1.png
- text: 'a beautifully crafted portrait of a woman, highlighting her natural beauty and unique features'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_28_0.png
- text: 'a beautifully crafted portrait of a woman, highlighting her natural beauty and unique features'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_29_1.png
- text: 'a powerful and striking portrait of a man, capturing his strength and character'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_30_0.png
- text: 'a powerful and striking portrait of a man, capturing his strength and character'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_31_1.png
- text: 'a playful and spirited portrait of a boy, capturing youthful energy and innocence'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_32_0.png
- text: 'a playful and spirited portrait of a boy, capturing youthful energy and innocence'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_33_1.png
- text: 'a charming and vibrant portrait of a girl, emphasizing her bright personality and joy'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_34_0.png
- text: 'a charming and vibrant portrait of a girl, emphasizing her bright personality and joy'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_35_1.png
- text: 'a heartwarming and cohesive family portrait, showcasing the bonds and connections between loved ones'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_36_0.png
- text: 'a heartwarming and cohesive family portrait, showcasing the bonds and connections between loved ones'
  parameters:
    negative_prompt: 'blurry, cropped, ugly'
  output:
    url: ./assets/image_37_1.png
---

# simpletuner-sana-lora-mikrei-1e-5

This is a LyCORIS adapter derived from [terminusresearch/sana-1.6b-1024px](https://huggingface.co/terminusresearch/sana-1.6b-1024px).


No validation prompt was used during training.

None



## Validation settings
- CFG: `4.0`
- CFG Rescale: `0.0`
- Steps: `30`
- Sampler: `sana`
- Seed: `42`
- Resolutions: `1024x1024,1280x768`


Note: The validation settings are not necessarily the same as the [training settings](#training-settings).

You can find some example images in the following gallery:


<Gallery />

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


## Training settings

- Training epochs: 0
- Training steps: 4500
- Learning rate: 1e-05
  - Learning rate schedule: polynomial
  - Warmup steps: 100
- Max grad norm: 2.0
- Effective batch size: 1
  - Micro-batch size: 1
  - Gradient accumulation steps: 1
  - Number of GPUs: 1
- Gradient checkpointing: False
- Prediction type: epsilon (extra parameters=['training_scheduler_timestep_spacing=trailing', 'inference_scheduler_timestep_spacing=trailing'])
- Optimizer: optimi-stableadamw
- Trainable parameter precision: Pure BF16
- Caption dropout probability: 10.0%


### LyCORIS Config:
```json
{
    "algo": "lokr",
    "multiplier": 1.0,
    "linear_dim": 10000,
    "linear_alpha": 1,
    "factor": 16,
    "apply_preset": {
        "target_module": [
            "Attention",
            "FeedForward"
        ],
        "module_algo_map": {
            "Attention": {
                "factor": 16
            },
            "FeedForward": {
                "factor": 8
            }
        }
    }
}
```

## Datasets

### mikrei-data-512px
- Repeats: 1000
- Total number of images: 17
- Total number of aspect buckets: 1
- Resolution: 0.262144 megapixels
- Cropped: False
- Crop style: None
- Crop aspect: None
- Used for regularisation data: No


## Inference


```python
import torch
from diffusers import DiffusionPipeline
from lycoris import create_lycoris_from_weights


def download_adapter(repo_id: str):
    import os
    from huggingface_hub import hf_hub_download
    adapter_filename = "pytorch_lora_weights.safetensors"
    cache_dir = os.environ.get('HF_PATH', os.path.expanduser('~/.cache/huggingface/hub/models'))
    cleaned_adapter_path = repo_id.replace("/", "_").replace("\\", "_").replace(":", "_")
    path_to_adapter = os.path.join(cache_dir, cleaned_adapter_path)
    path_to_adapter_file = os.path.join(path_to_adapter, adapter_filename)
    os.makedirs(path_to_adapter, exist_ok=True)
    hf_hub_download(
        repo_id=repo_id, filename=adapter_filename, local_dir=path_to_adapter
    )

    return path_to_adapter_file
    
model_id = 'terminusresearch/sana-1.6b-1024px'
adapter_repo_id = 'mtreinik/simpletuner-sana-lora-mikrei-1e-5'
adapter_filename = 'pytorch_lora_weights.safetensors'
adapter_file_path = download_adapter(repo_id=adapter_repo_id)
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16) # loading directly in bf16
lora_scale = 1.0
wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_file_path, pipeline.transformer)
wrapper.merge_to()

prompt = "An astronaut is riding a horse through the jungles of Thailand."
negative_prompt = 'blurry, cropped, ugly'

## Optional: quantise the model to save on vram.
## Note: The model was quantised during training, and so it is recommended to do the same during inference time.
from optimum.quanto import quantize, freeze, qint8
quantize(pipeline.transformer, weights=qint8)
freeze(pipeline.transformer)
    
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') # the pipeline is already in its target precision level
image = pipeline(
    prompt=prompt,
    negative_prompt=negative_prompt,
    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(42),
    width=1024,
    height=1024,
    guidance_scale=4.0,
    guidance_rescale=0.0,
).images[0]
image.save("output.png", format="PNG")
```



## Exponential Moving Average (EMA)

SimpleTuner generates a safetensors variant of the EMA weights and a pt file.

The safetensors file is intended to be used for inference, and the pt file is for continuing finetuning.

The EMA model may provide a more well-rounded result, but typically will feel undertrained compared to the full model as it is a running decayed average of the model weights.