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Zach001/yutu-krea2-lora
yutu-krea2-lora is a text-to-image model from Zach001. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
These are Zach001/yutu-krea2-lora DreamBooth LoRA weights, trained on krea/Krea-2-Raw.
The weights were trained using DreamBooth with the Krea 2 diffusers trainer.
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 — LoRAs trained on RAW express strongly on Turbo.
You should use a photo of yutu to trigger the image generation.
Download the *.safetensors LoRA in the Files & versions tab.
>>> 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("Zach001/yutu-krea2-lora")
>>> # Turbo recipe: 8 steps, no classifier-free guidance
>>> image = pipe("a photo of yutu", num_inference_steps=8, guidance_scale=0.0).images[0]
>>> image.save("output.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
# TODO: add an example code snippet for running this diffusion pipeline
[TODO: provide examples of latent issues and potential remediations]
[TODO: describe the data used to train the model]