Text-to-Image
Diffusers
image-generation
comfyui
quantization
int8
int4
svdquant
krea2
krea
diffusion
transformer
lowvram
Instructions to use AlperKTS/Krea-2-SVDQuant-ComfyUI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlperKTS/Krea-2-SVDQuant-ComfyUI with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AlperKTS/Krea-2-SVDQuant-ComfyUI", torch_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
| from .svdquant_capture import ( | |
| NODE_CLASS_MAPPINGS as _CAPTURE_NODES, | |
| NODE_DISPLAY_NAME_MAPPINGS as _CAPTURE_NAMES, | |
| ) | |
| from .svdquant_diag import ( | |
| NODE_CLASS_MAPPINGS as _DIAG_NODES, | |
| NODE_DISPLAY_NAME_MAPPINGS as _DIAG_NAMES, | |
| ) | |
| from .svdquant_lora import ( | |
| NODE_CLASS_MAPPINGS as _LORA_NODES, | |
| NODE_DISPLAY_NAME_MAPPINGS as _LORA_NAMES, | |
| ) | |
| from .svdquant_quantize import ( | |
| NODE_CLASS_MAPPINGS as _QUANT_NODES, | |
| NODE_DISPLAY_NAME_MAPPINGS as _QUANT_NAMES, | |
| ) | |
| from .svdquant_w4a4 import ( | |
| NODE_CLASS_MAPPINGS as _W4A4_NODES, | |
| NODE_DISPLAY_NAME_MAPPINGS as _W4A4_NAMES, | |
| ) | |
| NODE_CLASS_MAPPINGS = {**_LORA_NODES, **_W4A4_NODES, **_DIAG_NODES, **_QUANT_NODES, | |
| **_CAPTURE_NODES} | |
| NODE_DISPLAY_NAME_MAPPINGS = {**_LORA_NAMES, **_W4A4_NAMES, **_DIAG_NAMES, **_QUANT_NAMES, | |
| **_CAPTURE_NAMES} | |
| __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"] | |