Instructions to use hodgy/katherine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hodgy/katherine 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-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hodgy/katherine") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Katherinne โ Krea 2 Turbo LoRA
An identity/character LoRA for krea/Krea-2-Turbo, trained with Ostris AI Toolkit.
Trigger word
Use katherinne near the beginning of the prompt. This spelling matches the embedded model name and filename.
Example prompt:
Photorealistic portrait of katherinne, natural daylight, realistic skin texture, detailed eyes, shallow depth of field.
Training metadata
| Parameter | Value |
|---|---|
| Base family | Krea 2 |
| Training steps | 1000 |
| Recorded epoch | 8 |
| Trainer | ostris/ai-toolkit 0.11.1 |
| Tensor count | 512 |
File
katherinne_Krea-2-Turbo_lora.safetensors
The weights use AI Toolkit-style Krea 2 LoRA tensor names. Use a compatible Krea 2 workflow/loader.
Recommended settings
- Start around LoRA strength
0.8; adjust within approximately0.6โ1.0. - Put
katherinneonce in the subject description. - Describe pose, clothing, framing, lighting, and environment explicitly.
Limitations and responsible use
The dataset and learning rate are not included in the repository. Results can vary with framing, occlusion, stylization, and strength. Use only with the necessary rights and permission; do not impersonate, deceive, harass, exploit, or violate privacy or publicity rights. Disclose synthetic imagery where viewers could mistake it for reality.
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