Text-to-Image
Diffusers
Safetensors
Flux2KleinPipeline
colab
kaggle
jupyter
klein
9b
image_edit
text-generation-inference
sdnq
quantization
T4
notebook
batch_edit
16GB
LoRa
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
- Draw Things
- DiffusionBee
- Xet hash:
- 4c88adde2b0936f05dbc7d09e3701b2764507059c6510ab326f8df22c4ecc237
- Size of remote file:
- 168 MB
- SHA256:
- ca70d2202afe6415bdbcb8793ba8cd99fd159cfe6192381504d6c4d3036e0f04
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