Text-to-Image
Diffusers
Safetensors
English
Flux2KleinPipeline
art
stable-diffusion
flux
nf4
asset-editor
Instructions to use Veetance/FLUX-Klein-4B-NF4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Veetance/FLUX-Klein-4B-NF4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Veetance/FLUX-Klein-4B-NF4", 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
- Draw Things
- DiffusionBee
FLUX-Klein-4B-NF4 | Debloated
This repository contains the FLUX Klein 4B weights, quantized to 4-bit NF4 for the Asset Editor runtime.
Model Details
- Architecture: FLUX.1 Schnell distilled
- Quantization: NF4 (NormalFloat 4-bit)
- Primary use: lightweight asset generation on low-VRAM hardware
- License: Apache-2.0
Integration
Optimized for the Asset Editor Zerodrag pipeline.
Links
- Core engine: Veetance Asset Editor
- Triage and development: Asset Editor GitHub
This is a specialized runtime manifold for the Veetance Asset Editor stack.
- Downloads last month
- 12