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
File size: 446 Bytes
b7c53ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "Flux2KleinPipeline",
"_diffusers_version": "0.37.0.dev0",
"is_distilled": true,
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"Qwen3ForCausalLM"
],
"tokenizer": [
"transformers",
"Qwen2TokenizerFast"
],
"transformer": [
"diffusers",
"Flux2Transformer2DModel"
],
"vae": [
"diffusers",
"AutoencoderKLFlux2"
]
}
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