Instructions to use Keltezaa/KLEIN_Unchained_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Keltezaa/KLEIN_Unchained_V2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-base-9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Keltezaa/KLEIN_Unchained_V2") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Keltezaa/KLEIN_Unchained_V2: direct link, hf CLI and curl.
- Browser
- Download file 379 Bytes
-
https://huggingface.co/Keltezaa/KLEIN_Unchained_V2/resolve/main/README.md
- Command line
-
hf download hf://Keltezaa/KLEIN_Unchained_V2/README.md
-
curl -L -o README.md https://huggingface.co/Keltezaa/KLEIN_Unchained_V2/resolve/main/README.md
379 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/Unchained XXX.png
text: '-'
base_model: black-forest-labs/FLUX.2-klein-base-9B
instance_prompt: null
license: cc-by-nc-nd-4.0
KLEIN-Unchained-V2

- Prompt
- -
Download model
Download them in the Files & versions tab.