Krea 2 DreamBooth LoRA β€” yarn art style

Prompt
a cute puppy, yarn art style
Prompt
a steaming bowl of ramen with chopsticks, yarn art style
Prompt
a hummingbird hovering over a bright flower, yarn art style
Prompt
a tiger prowling through a jungle, yarn art style

Model description

A yarn art style LoRA for Krea 2, trained with the Krea 2 diffusers trainer on the Norod78/Yarn-art-style dataset.

Training config: rank 64 / alpha 64, the full default layer set, learning rate 3e-4 (constant), 1000 steps.

Krea 2 ships as two checkpoints: RAW (the non-distilled base you fine-tune on) and Turbo (an 8-step distilled checkpoint for fast, high-quality inference). Train your LoRA on RAW and run it on Turbo β€” LoRAs trained on RAW express strongly on Turbo.

Trigger words

You should use yarn art style to trigger the image generation.

Use it with the 🧨 diffusers library

>>> import torch
>>> from diffusers import Krea2Pipeline

>>> # Load the LoRA onto Krea 2 Turbo (the distilled inference model)
>>> pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
>>> pipe.load_lora_weights("linoyts/krea2-yarn-art-lora")

>>> # Turbo recipe: 8 steps, no classifier-free guidance
>>> image = pipe("a tiger prowling through a jungle, yarn art style", num_inference_steps=8, guidance_scale=0.0).images[0]
>>> image.save("output.png")

For more details on loading, weighting, merging and fusing LoRAs, see the diffusers LoRA docs.

Downloads last month
62
Inference Examples
Examples
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for linoyts/krea2-yarn-art-lora

Base model

krea/Krea-2-Raw
Adapter
(1111)
this model

Dataset used to train linoyts/krea2-yarn-art-lora