metadata
language:
- en
license: other
license_name: krea-2-community-license
license_link: >-
https://huggingface.co/OzzyGT/Krea_2_Turbo_sdnq_dynamic_4bit/blob/main/LICENSE.pdf
base_model:
- krea/Krea-2-Turbo
base_model_relation: quantized
tags:
- image-generation
- krea2
- sdnq
pipeline_tag: text-to-image
library_name: diffusers
Krea 2 Turbo SDNQ Dynamic INT4
Left: original bf16 · Right: this SDNQ int4 model (same prompt and seed).
This is an int4 quantized version of krea/Krea-2-Turbo using SDNQ (SD.Next Quantization) with the dynamic option and Hadamard Rotation.
Note: You need SDNQ v0.2.0 or v0.2.2 and above (v0.2.1 is incompatible)
Usage
You can find ready-to-use scripts in the diffusers-recipes repository.
Sample image
The quantized (right) image above was generated with the following prompt and settings (seed 7):
import sdnq # register the SDNQ backend before loading
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("OzzyGT/Krea_2_Turbo_sdnq_dynamic_4bit", torch_dtype=torch.bfloat16)
pipe.to("cuda")
prompt = (
"A cozy corner bookstore-cafe on a rainy evening, cinematic wide shot. "
'A large hand-lettered chalkboard sign in the window reads "FRESH COFFEE & OLD BOOKS" '
"and below it in smaller chalk letters \"open 'til late\". "
"Warm golden light spills onto wet cobblestones that mirror pink and blue neon reflections. "
"Inside, tall mahogany shelves are packed with hundreds of colorful book spines with tiny legible titles, "
"a barista in a striped apron pours delicate latte art, steam curling upward, "
"a tabby cat sleeps on a windowsill beside a stack of paperbacks. "
"Intricate detail, sharp focus, shallow depth of field, photorealistic, rich color grading."
)
image = pipe(
prompt,
num_inference_steps=8,
guidance_scale=0.0,
height=1024,
width=1024,
generator=torch.Generator("cuda").manual_seed(7),
).images[0]
image.save("sample.png")