Instructions to use loradica/lorarafa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use loradica/lorarafa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("loradica/lorarafa") prompt = "RafaelValente, casual portrait of a young Brazilian man, short beard, realistic photography" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from loradica/lorarafa: direct link, hf CLI and curl.
- Browser
- Download file 543 Bytes
-
https://huggingface.co/loradica/lorarafa/resolve/main/README.md
- Command line
-
hf download hf://loradica/lorarafa/README.md
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curl -L -o README.md https://huggingface.co/loradica/lorarafa/resolve/main/README.md
543 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/step_1500_validation_0_1024x1024.png
text: >-
RafaelValente, casual portrait of a young Brazilian man, short beard,
realistic photography
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: RafaelValente
lorarafa

- Prompt
- RafaelValente, casual portrait of a young Brazilian man, short beard, realistic photography
Trigger words
You should use RafaelValente to trigger the image generation.
Download model
Download them in the Files & versions tab.