Text-to-Image
Diffusers
Safetensors
English
Krea2Pipeline
image-generation
krea2
sdnq
8-bit precision
Instructions to use OzzyGT/Krea_2_Turbo_sdnq_dynamic_4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/Krea_2_Turbo_sdnq_dynamic_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("OzzyGT/Krea_2_Turbo_sdnq_dynamic_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
Upload README.md
Browse files
README.md
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# Krea 2 Turbo SDNQ Dynamic INT4
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This is an int4 quantized version of [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo) using [SDNQ](https://github.com/Disty0/sdnq) (SD.Next Quantization) with the dynamic option and Hadamard Rotation.
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Note: You need SDNQ v0.2.0 or v0.2.2 and above (v0.2.1 is incompatible)
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## Sample image
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The sample above was generated with the following prompt and settings (seed `7`):
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```python
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import sdnq # register the SDNQ backend before loading
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---
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# Krea 2 Turbo SDNQ Dynamic INT4
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*Left: original bf16 路 Right: this SDNQ int4 model (same prompt and seed).*
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This is an int4 quantized version of [krea/Krea-2-Turbo](https://huggingface.co/krea/Krea-2-Turbo) using [SDNQ](https://github.com/Disty0/sdnq) (SD.Next Quantization) with the dynamic option and Hadamard Rotation.
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Note: You need SDNQ v0.2.0 or v0.2.2 and above (v0.2.1 is incompatible)
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## Sample image
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The quantized (right) image above was generated with the following prompt and settings (seed `7`):
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```python
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import sdnq # register the SDNQ backend before loading
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