Text-to-Image
Diffusers
Safetensors
Flux2KleinPipeline
colab
kaggle
jupyter
klein
9b
image_edit
text-generation-inference
sdnq
quantization
T4
notebook
batch_edit
16GB
LoRa
8-bit precision
Instructions to use codeShare/FLUX.2-klein-9b-SDNQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codeShare/FLUX.2-klein-9b-SDNQ-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("codeShare/FLUX.2-klein-9b-SDNQ-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
- Xet hash:
- 09a6b4c9f6ad20f287163b79c980a0b6489911a22788785a0402821f5a914264
- Size of remote file:
- 6.84 GB
- SHA256:
- 2461c3f756edec000ebd5d0315c43811024ff91be72496b67e7d9be606a3c1be
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