Instructions to use mju75/eva-lora-weights-dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mju75/eva-lora-weights-dataset with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mju75/eva-lora-weights-dataset") prompt = "A cinematic shot of a futuristic cyborg 3va lounging in a neon-lit cyberpunk cafe, sipping iridescent tea amidst floating holographic displays." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA — mju75/eva-lora-weights-dataset

- Prompt
- A cinematic shot of a futuristic cyborg 3va lounging in a neon-lit cyberpunk cafe, sipping iridescent tea amidst floating holographic displays.

- Prompt
- A whimsical oil painting of a tiny forest sprite 3va napping inside a dew-covered peony flower during a golden sunrise.

- Prompt
- An epic wide shot of a majestic stone golem 3va standing guard at the entrance of a frozen crystalline temple under a swirling aurora borealis.
A DreamBooth-LoRA for Krea 2, trained on Krea 2 RAW and shown on Krea 2 Turbo. The samples below were generated with this LoRA on Turbo (8 steps).
Trigger
Use the token 3va to invoke the concept.
Samples
"A cinematic shot of a futuristic cyborg 3va lounging in a neon-lit cyberpunk cafe, sipping iridescent tea amidst floating holographic displays."
"A whimsical oil painting of a tiny forest sprite 3va napping inside a dew-covered peony flower during a golden sunrise."
"An epic wide shot of a majestic stone golem 3va standing guard at the entrance of a frozen crystalline temple under a swirling aurora borealis."
Use it with diffusers
import torch
from diffusers import Krea2Pipeline
pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("mju75/eva-lora-weights-dataset")
image = pipe("A cinematic shot of a futuristic cyborg 3va lounging in a neon-lit cyberpunk cafe, sipping iridescent tea amidst floating holographic displays.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
- Downloads last month
- 6
Model tree for mju75/eva-lora-weights-dataset
Base model
krea/Krea-2-Raw

