Text-to-Image
Diffusers
Krea2Pipeline
custom_krea2
image-generation
quantized
4-bit precision
int4
turbo
krea
krea-2
quantfunc
comfyui
Instructions to use QuantFunc/Krea-2-QuantFunc-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QuantFunc/Krea-2-QuantFunc-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("QuantFunc/Krea-2-QuantFunc-4bit", 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
File size: 405 Bytes
832d1b5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"model_type": "custom_krea2",
"architectures": [
"Krea2Pipeline"
],
"name_or_path": "QuantFunc/Krea-2-QuantFunc-4bit",
"task": "text-to-image",
"framework": "quantfunc",
"license": "other",
"description": "Pre-quantized Krea-2-Turbo image model by QuantFunc",
"_comment": "This is a minimal config to enable download stats on HF Hub. Not used for loading."
}
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