Instructions to use JunhaH/trained-flux-lora-768_2e-6_debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JunhaH/trained-flux-lora-768_2e-6_debug 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("JunhaH/trained-flux-lora-768_2e-6_debug") prompt = "A photo of sks beautiful korean woman, high quality, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Flux DreamBooth LoRA - JunhaH/trained-flux-lora-768_2e-6_debug

- Prompt
- A photo of sks beautiful korean woman, high quality, 8k

- Prompt
- A photo of sks beautiful korean woman, high quality, 8k

- Prompt
- A photo of sks beautiful korean woman, high quality, 8k

- Prompt
- A photo of sks beautiful korean woman, high quality, 8k
Model description
These are JunhaH/trained-flux-lora-768_2e-6_debug DreamBooth LoRA weights for black-forest-labs/FLUX.1-dev.
The weights were trained using DreamBooth with the Flux diffusers trainer.
Was LoRA for the text encoder enabled? False.
Trigger words
You should use women_prompt.txt 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.1-dev", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('JunhaH/trained-flux-lora-768_2e-6_debug', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('A photo of sks beautiful korean woman, high quality, 8k').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 JunhaH/trained-flux-lora-768_2e-6_debug
Base model
black-forest-labs/FLUX.1-dev