Instructions to use SamuelTallet/Krea-2-Turbo-SDNQ-3bit-dynamic-hadamard256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SamuelTallet/Krea-2-Turbo-SDNQ-3bit-dynamic-hadamard256 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SamuelTallet/Krea-2-Turbo-SDNQ-3bit-dynamic-hadamard256", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
This is Krea 2 Turbo optimized using SDNQ with UINT3 dynamic quantization and Hadamard Rotation (Group size: 256).
Sample
Prompt:
A heavily burdened, blue-skinned warrior wanders through a starry dreamscape in a detailed 2D illustration merging sci-fi and feudal fantasy aesthetics. Viewed in profile facing left, the figure features mottled skin, a dark half-mask with gold accents, and an elongated blue headpiece. They wear a complex, patched tunic with a thick brown fur mantle, carrying two ornately hilted katanas at the hip. A towering pack strapped to their back is lashed with thick ropes, securing gourds, wrapped bundles, and swirling cyan vapor. The foreground holds pale blue plants against a gradient sky transitioning from deep indigo to bright cyan. White stars and a massive dark blue crescent shape frame the character, rendered with vivid cel-shaded coloring and intricate line art.
Seed: 42
Usage
Install Torch, Diffusers (Git), SDNQ 0.2.0 and Triton.
Use CFG 0 and 8 steps.
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