🐱🐺 Понравилось? <a target="_blank" rel="ugc" href="https://civarchive.com/user/bazya022020810">Заходи за другими</a>100% AI-generated fictional character (OC). Does not depict or reference any real person.KREA 2This LoRA is the product of creative dataset experiments and workflow stress-testing. It was originally built as a testbed to train and seamlessly bake multiple intricate elements into a single model without distortion: vivid colorful neck and thigh tattoos, realistic multi-strand pearl chokers, distinct two-tone hair bangs, and consistent facial features across vastly different clothing and environments.MOSSБолее ранняя версияThis model received technical support from ModelScope.

FEKLA   [MOSS / Krea]

FeklaQ.safetensors

v1.0 Qwen 2.1

v1.0 MOSS

v1.0 Krea 2


# 

## Model Introduction

This model is trained using the [Civision/model training](https://modelscope.ai/civision/modelTraining) environment and computing resources provided by ModelScope.

* Model Type: LoRA
* Base Model: [Qwen/Qwen-Image-2.1](https://modelscope.ai/models/Qwen/Qwen-Image-2.1)
* Training Code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Data amount：22
* Total training steps：2000
* License: Apache-2.0

## Inference Code

Install [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio):

```bash
pip install diffsynth
```

Inference:

```python
from diffsynth.pipelines.qwen_image_21 import QwenImage21Pipeline, ModelConfig
import torch

pipe = QwenImage21Pipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="Qwen/Qwen-Image-2.1", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
        ModelConfig(model_id="Qwen/Qwen-Image-2.1", origin_file_pattern="text_encoder/model*.safetensors"),
        ModelConfig(model_id="Qwen/Qwen-Image-2.1", origin_file_pattern="vae/diffusion_pytorch_model*.safetensors"),
    ],
    processor_config=ModelConfig(model_id="Qwen/Qwen-Image-2.1", origin_file_pattern="processor/"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="bazya75/MotV2Q", origin_file_pattern="MotV2Q_c1-st2000.safetensors"))

prompt = "a cat"
image = pipe(prompt, seed=0, num_inference_steps=50)
image.save("image.png")
```


Files with SHA256: 8ef37569f8f7c8dcb5aa786fe5aec6255330d8ca9d5979928e0456ec787c510b