Instructions to use codeShare/Klein9B-DarkBeast-SDNQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/Klein9B-DarkBeast-SDNQ-4bit with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("codeShare/Klein9B-DarkBeast-SDNQ-4bit", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
👷 Note! The transformer part of this repo is work in progress! If you want to use darkbeast klein model 9b I suggest using base model with extracted lora in meantime , available at https://huggingface.co/codeShare/FLUX.2-klein-9b-SDNQ-4bit/tree/main/colab_notebooks
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