Instructions to use Nanico/bbm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nanico/bbm 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("Nanico/bbm") prompt = "A futuristic cyberpunk cityscape at midnight with neon rain, featuring a sleek chrome robot holding a glowing bbm device." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ Nanico/bbm

- Prompt
- A futuristic cyberpunk cityscape at midnight with neon rain, featuring a sleek chrome robot holding a glowing bbm device.

- Prompt
- A serene sun-drenched Tuscan vineyard with rolling hills, where a rustic wooden table holds a vintage bbm artifact.

- Prompt
- A surreal deep-sea kingdom with bioluminescent coral reefs and a majestic whale wearing a golden bbm crown.
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 bbm to invoke the concept.
Samples
"A futuristic cyberpunk cityscape at midnight with neon rain, featuring a sleek chrome robot holding a glowing bbm device."
"A serene sun-drenched Tuscan vineyard with rolling hills, where a rustic wooden table holds a vintage bbm artifact."
"A surreal deep-sea kingdom with bioluminescent coral reefs and a majestic whale wearing a golden bbm crown."
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("Nanico/bbm")
image = pipe("A futuristic cyberpunk cityscape at midnight with neon rain, featuring a sleek chrome robot holding a glowing bbm device.", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for Nanico/bbm
Base model
krea/Krea-2-Raw

