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
- Draw Things
- DiffusionBee
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d5595db1-0f31-48c6-8588-77127c417be8.TA_trained (1).safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4fdfdbbad5a973409d8b5347d529953cc322d41e3c80f7708eeb3afc62ef0acd
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size 67286020
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images/textportrait, A stylized portrait of Angelina J....png
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Git LFS Details
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