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---
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: 'Photography, upper body, yellow hue, woman model, solid yellow backdrop, yellow eyes detailing, using a camera setup that mimics a large aperture, f/1.4 --ar 9:16 --style raw'
  output:
    url: images/ps1.png
- text: 'Young red-haired man, in turtleneck shirt, gold color, dynamic pose, side view, light background, front lighting, medium shot, high quality photo --ar 2:3 --v 5'
  output:
    url: images/ps2.png
- text: 'A photo of an attractive man in his thirties, wearing a black coat and yellow scarf with a brown pattern inside a building talking on a phone standing near a modern glass skyscraper in London, shot from below looking up at him in the style of street photography, cinematic.  --ar 85:128 --v 6.0 --style raw'
  output:
    url: images/ps3.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: Photo Shoot
license: creativeml-openrail-m
---
# Photo-Shoot-Mini-LoRA

<Gallery />


## Model description 

Canopus-Photo-Shoot-Mini-LoRA

Image Processing Parameters 

| Parameter                 | Value  | Parameter                 | Value  |
|---------------------------|--------|---------------------------|--------|
| LR Scheduler              | constant | Noise Offset              | 0.03   |
| Optimizer                 | AdamW  | Multires Noise Discount   | 0.1    |
| Network Dim               | 64     | Multires Noise Iterations | 10     |
| Network Alpha             | 32     | Repeat                    | 27     |
| Epoch                     | 20     | Save Every N Epochs       | 1      |

## SETTING-UP

```py
    pipe = StableDiffusionXLPipeline.from_pretrained(
        "-------------xxxxxxxxx----------",
        torch_dtype=torch.float16,
        use_safetensors=True,
    )
                    (or)
-----------------------------------------------------------
    pipe = StableDiffusionXLPipeline.from_pretrained(
        "stabilityai/stable-diffusion-xl-base-1.0",
        torch_dtype=torch.float16,
        use_safetensors=True,
    )
    pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
    
    pipe.load_lora_weights("prithivMLmods/Canopus-Photo-Shoot-Mini-LoRA", weight_name="Canopus-Photo-Shoot-Mini-LoRA.safetensors", adapter_name="photo")
    pipe.set_adapters("photo")
    pipe.to("cuda")
```


## Trigger prompts

    Photography, upper body, yellow hue, woman model, solid yellow backdrop, yellow eyes detailing, using a camera setup that mimics a large aperture, f/1.4 --ar 9:16 --style raw


    Young red-haired man, in turtleneck shirt, gold color, dynamic pose, side view, light background, front lighting, medium shot, high quality photo --ar 2:3 --v 5


    A photo of an attractive man in his thirties, wearing a black coat and yellow scarf with a brown pattern inside a building talking on a phone standing near a modern glass skyscraper in London, shot from below looking up at him in the style of street photography, cinematic.  --ar 85:128 --v 6.0 --style raw

| Parameter       | Value                                                                                 |
|-----------------|---------------------------------------------------------------------------------------|
| Prompt          | Young red-haired man, in turtleneck shirt, gold color, dynamic pose, side view, light background, front lighting, medium shot, high quality photo --ar 2:3 --v 5 |
| Sampler         | euler                                                                                 |


## Trigger words

You should use `Photo Shoot` to trigger the image generation.


## Download model

Weights for this model are available in Safetensors format.

[Download](/prithivMLmods/Canopus-Photo-Shoot-Mini-LoRA/tree/main) them in the Files & versions tab.