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krystian-kaczor/
krystian-flux-avatar

Name: krystian-flux-avatar
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markdown

---
license: creativeml-openrail-m
base_model: black-forest-labs/FLUX.1-schnell
tags:
- flux
- lora
- text-to-image
- diffusers
- avatar
instance_prompt: "a photo of KAKI"
---

# LoRA for FLUX: krystian-flux-avatar

These are LoRA weights for the base model **[black-forest-labs/FLUX.1-schnell](https://huggingface.co/black-forest-labs/FLUX.1-schnell)**. The weights were trained on a custom dataset to generate images in a specific style, triggered by the word `KAKI`.

## How to use

First, make sure you have the `diffusers` library installed:
```bash
pip install diffusers transformers accelerate torch

Then, you can use the following Python code to load the base model and apply the LoRA weights.

python

import torch
from diffusers import FluxPipeline

# Load the base FLUX model
model_id = "black-forest-labs/FLUX.1-schnell"
pipe = FluxPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
pipe.to("cuda")

# Load the LoRA weights into the pipeline
lora_repo_id = "krystian-kaczor/krystian-flux-avatar"
pipe.load_lora_weights(lora_repo_id)

# Generate an image using the trigger word
prompt = "photo of a beautiful woman, KAKI style, cinematic, detailed, high resolution"

# Generate the image
image = pipe(
    prompt=prompt,
    num_inference_steps=8,
    guidance_scale=0,
).images[0]

# Save the image
image.save("generated_image.png")

print("Image saved as generated_image.png")

Trigger words

You should use KAKI in your prompt to trigger the LoRA. For best results, you can use it as "KAKI style" or simply "KAKI".

Training

These weights were trained on Replicate using the following parameters:

Model: krystian-kaczor/train-flux-lora
Input Images: Flux-Training-Data.zip
Training Steps: 1000
Trigger Word: KAKI
Seed: 999
Hugging Face Repo ID: krystian-kaczor/krystian-flux-avatar