metadata

base_model: black-forest-labs/FLUX.1-dev
library_name: diffusers
license: other
instance_prompt: a photo of sks dog
widget:
  - text: A photo of sks dog in a bucket
    output:
      url: image_0.png
  - text: A photo of sks dog in a bucket
    output:
      url: image_1.png
  - text: A photo of sks dog in a bucket
    output:
      url: image_2.png
  - text: A photo of sks dog in a bucket
    output:
      url: image_3.png
tags:
  - text-to-image
  - diffusers-training
  - diffusers
  - flux
  - flux-diffusers
  - template:sd-lora
  - text-to-image
  - diffusers-training
  - diffusers
  - flux
  - flux-diffusers
  - template:sd-lora

Flux [dev] DreamBooth - yangmjie/trained-flux

Model description

These are yangmjie/trained-flux DreamBooth weights for black-forest-labs/FLUX.1-dev.

The weights were trained using DreamBooth with the Flux diffusers trainer.

Was the text encoder fine-tuned? False.

Trigger words

You should use a photo of sks dog to trigger the image generation.

Use it with the 🧨 diffusers library

from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('yangmjie/trained-flux', torch_dtype=torch.bfloat16).to('cuda')
image = pipeline('A photo of sks dog in a bucket').images[0]

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]