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---
license: other
base_model: stabilityai/stable-diffusion-3.5-large
tags:
- sd3
- sd3-diffusers
- text-to-image
- diffusers
- simpletuner
- safe-for-work
- lora
- template:sd-lora
- standard
inference: true
widget:
- text: grey shirt with a small logo of a bunny painted in the alebrijeros style
output:
url: images/example_wr1vsmbx0.png
- text: hoodie with flowers painted in the alebrijeros style
output:
url: images/example_8srfnn37z.png
---
# sd3-lora-alebrijeros-final
Este es un LoRA derivado del modelo más reciente de stable diffusion:
[stabilityai/stable-diffusion-3.5-large](https://huggingface.co/stabilityai/stable-diffusion-3.5-large).
El prompt usado durante el entrenamiento:
```
sweatshirt painted in the alebrijeros style
```
You can find some example images in the following gallery:
<Gallery />
## Configuración del entrene
- Training epochs: 4
- Training steps: 2600
- Learning rate: 5e-05
- Max grad norm: 0.01
- Effective batch size: 1
- Micro-batch size: 1
- Gradient accumulation steps: 1
- Number of GPUs: 1
- Prediction type: flow-matching
- Rescaled betas zero SNR: False
- Optimizer: adamw_bf16
- Precision: Pure BF16
- Quantised: Yes: int8-quanto
- Xformers: Not used
- LoRA Rank: 64
- LoRA Alpha: None
- LoRA Dropout: 0.1
- LoRA initialisation style: default
## Datasets
Imágenes variadas obtenidas de google que incluyen desde un mercedes pintado por alebrijeros hasta miss universo que fue con un vestido estilo alebrijero
## Inference
```python
import torch
from diffusers import DiffusionPipeline
model_id = 'stabilityai/stable-diffusion-3.5-large'
adapter_id = 'CarlosRiverMe/sd3-lora-alebrijeros-final'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "sweatshirt painted in the alebrijeros style"
negative_prompt = 'blurry, cropped, ugly'
pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
image = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
num_inference_steps=20,
generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826),
width=512,
height=512,
guidance_scale=5.0,
).images[0]
image.save("output.png", format="PNG")
```
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