Krea 2 DreamBooth LoRA - Ghaxalll/ghaxal-face
A face LoRA of Ghazal, trained on 21 original iPhone photos (7.2 to 12.2 MP, straight from the
camera roll, never through a messenger).
Trigger word
Use ghaxal_woman in every prompt.
The auto-generated card first said TOK. That was a placeholder left by the training script,
not the real trigger. TOK will not produce this face.
What the captions deliberately leave out
The hair (short straight bob) is never named in any training caption, so it is baked into the
identity and arrives with the trigger word.
These were captioned, so they are optional and can be prompted away: red lanyard, sunglasses
resting on the head, large black bead necklace, backpack straps, wireless earbud, and every
location and lighting condition.
Checkpoints
| Path | Steps |
|---|
| pytorch_lora_weights.safetensors | 1000 (final) |
| checkpoint-1000/ | 1000 |
| checkpoint-500/ | 500 |
If the final weights look over-baked, try checkpoint-500 before retraining.
Ignore the sample images
sample_0.png, sample_1.png and sample_2.png show a white tiger, a library interior and another
generic scene. They came from the post-training showcase step, which generated style-type
prompts that never contained ghaxal_woman. They say nothing about this model, good or bad.
Use it with the diffusers library
1import torch
2from diffusers import Krea2Pipeline
3
4pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
5pipe.load_lora_weights("Ghaxalll/ghaxal-face")
6
7prompt = "ghaxal_woman, sitting at a desk by a window, soft afternoon light, 85mm"
8image = pipe(prompt, num_inference_steps=8, guidance_scale=0.0).images[0]
9image.save("output.png")
Training details
| Setting | Value |
|---|
| Base | krea/Krea-2-Raw |
| Method | DreamBooth LoRA |
| Images | 21 |
| Steps | 1000 |
| Resolution | 1024 |
| Dataset | Ghaxalll/ghaxal-face-dataset |
Limitations
Strong on head-and-shoulders framing; weaker at full body and true profile, because the training
set contained neither. All but one training image was a selfie, so camera distance barely varies.