Instructions to use PeterD69/portrait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PeterD69/portrait with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("PeterD69/portrait") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - flux | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - fal | |
| base_model: undefined | |
| instance_prompt: | |
| license: other | |
| # portrait | |
| <Gallery /> | |
| ## Model description | |
| ## Trigger words | |
| You should use `` to trigger the image generation. | |
| ## Download model | |
| Weights for this model are available in Safetensors format. | |
| [Download](/PeterD69/portrait/tree/main) them in the Files & versions tab. | |
| ## Training at fal.ai | |
| Training was done using [fal.ai/models/fal-ai/flux-lora-portrait-trainer](https://fal.ai/models/fal-ai/flux-lora-portrait-trainer). | |