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
Download model_index.json from QuantFunc/Krea-2-QuantFunc-4bit: direct link, hf CLI and curl.
- Browser
- Download file 187 Bytes
-
https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/model_index.json
- Command line
-
hf download hf://QuantFunc/Krea-2-QuantFunc-4bit/model_index.json
-
curl -L -o model_index.json https://huggingface.co/QuantFunc/Krea-2-QuantFunc-4bit/resolve/main/model_index.json
187 Bytes
| { | |
| "_class_name": "Krea2Pipeline", | |
| "_diffusers_version": "0.30.0", | |
| "_comment": "Minimal index enabling HF Hub download statistics. Loading uses the QuantFunc toolkit; see README." | |
| } | |