Instructions to use IEKOO/trained-flux2-klein-4b-pet_cat3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use IEKOO/trained-flux2-klein-4b-pet_cat3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-base-4B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("IEKOO/trained-flux2-klein-4b-pet_cat3") prompt = "a photo of sks cat sitting on a sofa" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Flux.2 [Klein] DreamBooth LoRA - IEKOO/trained-flux2-klein-4b-pet_cat3

- Prompt
- a photo of sks cat sitting on a sofa

- Prompt
- a photo of sks cat sitting on a sofa

- Prompt
- a photo of sks cat sitting on a sofa

- Prompt
- a photo of sks cat sitting on a sofa
Model description
These are IEKOO/trained-flux2-klein-4b-pet_cat3 DreamBooth LoRA weights for black-forest-labs/FLUX.2-klein-base-4B.
The weights were trained using DreamBooth with the Flux2 diffusers trainer.
Quant training? None
Trigger words
You should use a photo of sks cat to trigger the image generation.
Download model
Download the *.safetensors LoRA in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.2", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('IEKOO/trained-flux2-klein-4b-pet_cat3', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('a photo of sks cat sitting on a sofa').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
License
Please adhere to the licensing terms as described here.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for IEKOO/trained-flux2-klein-4b-pet_cat3
Base model
black-forest-labs/FLUX.2-klein-base-4B