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
Upload cm4l2m107013ln318d9a7xms9.safetensors
Browse files
cm4l2m107013ln318d9a7xms9.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2e66b2344e0190f97c204d340e931c96ecff260b8b6a0fd8ea0ea1d2224d0128
|
| 3 |
+
size 171969072
|