Instructions to use funseshon/ma-ds-facing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use funseshon/ma-ds-facing 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("funseshon/ma-ds-facing") prompt = "A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, MA_DS_FACING" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ funseshon/ma-ds-facing

- Prompt
- A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, MA_DS_FACING

- Prompt
- A sleek, futuristic chrome hover-car gliding down a neon-lit Tokyo highway at midnight, MA_DS_FACING

- Prompt
- An elderly clockmaker meticulously repairing a golden pocket watch in a dusty, sun-drenched attic workshop, MA_DS_FACING
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 phrase MA_DS_FACING to invoke the concept.
Samples
"A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, MA_DS_FACING"
"A sleek, futuristic chrome hover-car gliding down a neon-lit Tokyo highway at midnight, MA_DS_FACING"
"An elderly clockmaker meticulously repairing a golden pocket watch in a dusty, sun-drenched attic workshop, MA_DS_FACING"
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("funseshon/ma-ds-facing")
image = pipe("A majestic snow leopard leaping across a jagged Himalayan cliffside during a swirling blizzard, MA_DS_FACING", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for funseshon/ma-ds-facing
Base model
krea/Krea-2-Raw

