Instructions to use 24aittl/flux2-klein-9b-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 24aittl/flux2-klein-9b-merged with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("24aittl/flux2-klein-9b-merged", 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
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("24aittl/flux2-klein-9b-merged", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Merged FLUX.2 Klein 9B LoRA Model
This repository contains a FLUX.2 Klein 9B Diffusers pipeline with LoRA adapters fused into the base weights.
Base model: black-forest-labs/FLUX.2-klein-9B
Merged adapters:
pytorch_lora_weights.safetensorsaslora_0with weight1.0corev3_klein_v3_v5.safetensorsaslora_1with weight1.0
The LoRA layers were fused with Flux2KleinPipeline.fuse_lora and unloaded before saving.
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