Instructions to use jayark/sammy-krea-v5-loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jayark/sammy-krea-v5-loras 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jayark/sammy-krea-v5-loras") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Sammy Krea v5 LoRAs
Selected production candidates from the Sammy Krea v5 checkpoint evaluation:
- Character identity: step 800, trigger
sammy - General visual style: step 1400, trigger
sammy style
Fal-compatible files
Use the files in fal-compatible/ with fal-ai/krea-2/turbo/lora. They use
Diffusers-style Krea 2 LoRA keys and were verified through Fal's queue API.
fal-compatible/sammy-character-krea2-v5-step800.safetensors- SHA256:
2427e1344033434a0e18e81f11c01762c947b9464480c71db4b2583b18a810e6
- SHA256:
fal-compatible/sammy-style-krea2-v5-step1400.safetensors- SHA256:
551d60ec904e9c677750dcad97143cb563c712bf33fb2967f7d846126176dc2b
- SHA256:
The root-level checkpoints are the original musubi-tuner outputs. They work in the native musubi inference pipeline but must not be passed directly to Fal's managed Krea 2 endpoint. Fal can accept those URLs without applying the weights.
The adapter weights are subject to the Krea 2 base model's community license and any applicable rights in the training material.
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