Instructions to use Leon1000/pixel_portrait_lora_v1-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Leon1000/pixel_portrait_lora_v1-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Leon1000/pixel_portrait_lora_v1-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| - ai-toolkit | |
| base_model: Qwen/Qwen-Image | |
| license: creativeml-openrail-m | |
| inference: | |
| parameters: | |
| width: 512 | |
| height: 512 | |
| # pixel_portrait_lora_v1-lora | |
| Model trained with [AI Toolkit by Ostris](https://github.com/ostris/ai-toolkit) | |
| ## Trigger words | |
| No trigger words defined, but it's recommended to start with "*A portrait of \[subject\] with \[appearance/traits\]*". | |
| ## Sample outputs | |
| Images from left-to-right were generated at 512x512 with: | |
| No LoRA, 500 steps, 1000 steps, 1500 steps, 2000 steps (final checkpoint) | |
| ### Medieval Knight | |
| **Prompt**: *A portrait of a medieval knight with iron armor, wearing a full iron helmet with a red plume on the back side of the helm. The knight is facing front right at a 45-degree angle with a neutral pose. The iron armor is clean and reflective, showing a clean polish.* | |
|  | |
| ### Witch | |
| **Prompt**: *A portrait of a witch with long red hair and blue eyes, wearing a dark purple witch hat and robes. The witch is facing left with a neutral expression. The robes are trimmed with white and light purple colors.* | |
|  | |
| ### Werewolf | |
| **Prompt**: *A portrait of a werewolf with light gray fur and yellow eyes, wearing a red scarf and a sword on his back. The werewolf is facing forward with a confident expression.* | |
|  | |
| ## How to get pixel-perfect images | |
| To get pixel-perfect images, downscale by a factor of 8. So 512x512 images should downscale to 64x64, 1024x1024 to 128x128, and so on. | |
| You can generate at higher resolutions like 1024x1024, but you may get worse pixel quality because the LoRA was trained on 512x512 images only. | |
| ## Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc. | |
| Weights for this model are available in Safetensors format. | |
| [Download](svntax-dev/pixel_portrait_lora_v1-lora/tree/main) them in the Files & versions tab. | |
| ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) | |
| ```py | |
| from diffusers import AutoPipelineForText2Image | |
| import torch | |
| pipeline = AutoPipelineForText2Image.from_pretrained('Qwen/Qwen-Image', torch_dtype=torch.bfloat16).to('cuda') | |
| pipeline.load_lora_weights('svntax-dev/pixel_portrait_lora_v1-lora', weight_name='pixel_portrait_lora_v1_000001500.safetensors') | |
| image = pipeline('a beautiful landscape').images[0] | |
| image.save("my_image.png") | |
| ``` | |
| For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters) | |