Instructions to use den123/TextPortrait with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use den123/TextPortrait 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("den123/TextPortrait") prompt = "textportrait, A stylized portrait of Taylor Swift made entirely of texts in various colors, creating the contours of a woman's face. The image uses typography to define facial features, shadows, and hair against a black background, illustrating creative text art." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
textportrait

- Prompt
- textportrait, A stylized portrait of Taylor Swift made entirely of texts in various colors, creating the contours of a woman's face. The image uses typography to define facial features, shadows, and hair against a black background, illustrating creative text art.

- Prompt
- textportrait, A stylized portrait of Taylor Swift made entirely of texts in various colors, creating the contours of a woman's face. The image uses typography to define facial features, shadows, and hair against a black background, illustrating creative text art.
Trigger words
You should use textportrait to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for den123/TextPortrait
Base model
black-forest-labs/FLUX.1-schnell