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.
๐ท 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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