
# 

## 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: [briaai/Fibo-2.0-dev](https://modelscope.ai/models/briaai/Fibo-2.0-dev)
* Training Code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Data amount：70
* Total training steps：6000
* License: Apache-2.0

## Inference Code

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

```bash
pip install diffsynth
```

Inference:

```python
import torch
from diffsynth.pipelines.fibo import FiboPipeline, ModelConfig

pipe = FiboPipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="briaai/Fibo-2.0-dev", origin_file_pattern="transformer/*.safetensors"),
        ModelConfig(model_id="briaai/Fibo-2.0-dev", origin_file_pattern="text_encoder/model.safetensors"),
        ModelConfig(model_id="briaai/Fibo-2.0-dev", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
    ],
    processor_config=ModelConfig(model_id="briaai/Fibo-2.0-dev", origin_file_pattern="processor/"),
    font_config=ModelConfig(model_id="briaai/Fibo-2.0-dev", origin_file_pattern="fonts/"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="tostiok/tostiadv-dott-v3-fibo2", origin_file_pattern="tostiadv-dott-v3-fibo2_c2-st6000.safetensors"))

prompt = "a cat"
image = pipe(prompt=prompt, height=1024, width=1024, seed=0, num_inference_steps=50, cfg_scale=5.0)
image.save("image.png")
```


tostiadv-dott-v3-fibo2

tostiadv-dott-v3-fibo2_c2-st3000.safetensors

c2-st3000

Files with SHA256: 446a97fe298a5b120ca06273b5963e3cbb1c6e8a17bf91896be9cd047465a375