Instructions to use alvdansen/flux-koda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alvdansen/flux-koda 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.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("alvdansen/flux-koda") prompt = "woman, flmft kodachrome style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Can you share some training details?
#4
by YGSC - opened
Very nice LORA, I like it very much! Since I've recently been learning to train Flux LORA, could you please share some details about the training.
For example, the training tool you used, what was the composition of the dataset, how many images were used, and how did you tag the images?
Thanks a lot!
I would also appreciate. does this work with shnell ?
thanks