Instructions to use HarakaBaraka/meg-flux-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use HarakaBaraka/meg-flux-lora with PEFT:
Task type is invalid.
- Inference
- Notebooks
- Google Colab
- Kaggle
Meg the dog - Flux LoRA
This is a LoRA (Low-Rank Adaptation) model trained on images of Meg the dog using the Flux.1-dev base model.
Usage
from diffusers import DiffusionPipeline
import torch
# Load the base model
pipe = DiffusionPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
torch_dtype=torch.bfloat16
).to("cuda")
# Load the LoRA weights
pipe.load_lora_weights("HarakaBaraka/meg-flux-lora")
# Generate an image
prompt = "a photo of Meg the dog"
image = pipe(prompt, num_inference_steps=50, guidance_scale=6).images[0]
image.save("generated_image.png")
Training Details
- Base model: black-forest-labs/FLUX.1-dev
- Training steps: 500
- Learning rate: 0.0004
- LoRA rank: 16
- Resolution: 512px
Example Prompts
Try these prompts with your model:
Meg the doga painting of Meg the dog in the style of Van GoghMeg the dog wearing a superhero costumeoil painting of Meg the dog flying through space as an astronaut
Training Data
This model was trained on personal images. Please use responsibly and respect privacy.
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Model tree for HarakaBaraka/meg-flux-lora
Base model
black-forest-labs/FLUX.1-dev