lucataco / diffusers-dreambooth-lora

FLUX.1-Dev LoRA Training by Huggingface Diffusers

  • Public
  • 188 runs
  • A100 (80GB)
  • GitHub
  • License

Input

file

A zip file containing the images that will be used for training.

string
Shift + Return to add a new line

Instance prompt to trigger the image generation

Default: "a photo of TOK dog"

integer

The resolution for input images, all the images in the train/validation dataset will be resized to this

Default: 512

integer
(minimum: 100, maximum: 6000)

Total number of training steps to perform

Default: 500

integer
(minimum: 4, maximum: 64)

The dimension of the LoRA

Default: 4

string

The optimizer type to use

Default: "AdamW"

number
(minimum: 0.0001, maximum: 1)

Initial learning rate to use (1.0 for Prodigy)

Default: 0.0001

Including train_batch_size and 8 more...

Output

Generated in

Run time and cost

This model runs on Nvidia A100 (80GB) GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

Huggingface Diffusers Dreambooth LoRA Trainer for Flux.1-Dev

About

Cog implementation of the Diffusers Dreambooth LoRA Trainer

Follow me on Twitter/X @lucataco93

How to use

Upload images as a zip file to train a LoRA. For max_train_steps, 100 steps per image is recommended. For resolution, 512 is recommended

If you want to upload your trained LoRA to Huggingface, be sure to add a HF_token that has write access and choose a model location.

There is also a wandb option to track your training run.

An example of an uploaded LoRA can be found here: lucataco/flux-queso

Run your LoRA

Copy the URL from the trained_model.tar from the prediction output, and use the lucataco/flux-dev-lora Explorer model to run your LoRA

An example of a prediction run with a LoRA can be found here queso

Licensing and commercial use

If you generate images on Replicate with FLUX.1 models and their fine-tunes, then you can use the images commercially.

If you download the weights off Replicate and generate images on your own computer, you can’t use the images commercially.