Instructions to use vantagewithai/Krea-2-Raw-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vantagewithai/Krea-2-Raw-GGUF with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vantagewithai/Krea-2-Raw-GGUF", dtype=torch.bfloat16, device_map="cuda") prompt = "A small, dark-colored cat is captured mid-stride, walking down the center of a narrow, abandoned street. The street is paved and appears cracked and worn. On either side of the street are tall, dilapidated buildings with visible brickwork and windows. A street lamp stands on the right side. The entire image is rendered in a monochromatic blue, with a distinct halftone dot pattern overlaying the scene, giving it a retro or printed appearance. The focus is soft, and the lighting is diffused, creating a hazy, atmospheric effect. The perspective is from ground level, looking down the length of the street, which narrows into the distance., halftone texture" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d6d7b4962e00c887b3cab623b5c089a8d24bef00b377776065df2e3b70472d96
- Size of remote file:
- 6.01 GB
- SHA256:
- 7fd0a577a81310a277f0404d96d072e9b1dccc44e1fb042ac97ac827dee268b2
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