Instructions to use furaidosu/flux-lora-tstvctr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use furaidosu/flux-lora-tstvctr 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("furaidosu/flux-lora-tstvctr") prompt = "This image is a simplified, TSTVCTR vector-style portrait of a person with distinct cartoonish features. The man is wearing a gray hat and black-framed glasses. He has a thick, neatly trimmed beard and mustache. A playful touch is added by a small blue flower with a pink center placed behind his right ear. His expression is neutral, with a hint of warmth in his eyes and a faint smile. The background is a solid pale yellow, providing a calm, minimalistic backdrop that contrasts with the bold, dark colors of his beard and glasses. He is dressed in a simple green shirt, which matches the clean, modern, and flat art style of the image. The overall feel of the illustration is lighthearted and modern, with geometric lines and a focus on smooth, flat shapes. The flower adds a fun and quirky element to the otherwise calm and straightforward portrayal." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Add generated example
#16 opened over 1 year ago
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furaidosu
Update README.md
#1 opened over 1 year ago
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latostadaok