# How to Use

Fibo 2.0 uses a Fibo diffusion transformer, the standard FLUX.2 VAE, and Qwen3-VL 4B as the LLM text encoder. The Qwen tokenizer is built in.

## Download weights

- Download Fibo 2.0 Dev
    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/diffusion_models
- Download Fibo 2.0 Edit Turbo
    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/diffusion_models
- Download vae
    - safetensors: https://huggingface.co/black-forest-labs/FLUX.2-dev/tree/main
- Download Qwen3-VL 4B
    - safetensors: https://huggingface.co/Comfy-Org/Fibo-2.0/tree/main/text_encoders
    - gguf: https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct-GGUF/tree/main

The original Diffusers weights from [briaai/Fibo-2.0-dev](https://huggingface.co/briaai/Fibo-2.0-dev) and [briaai/Fibo-2.0-edit-turbo](https://huggingface.co/briaai/Fibo-2.0-edit-turbo) are also supported. Pass the transformer's `diffusion_pytorch_model.safetensors.index.json` to `--diffusion-model` and keep its shards alongside it.

INT8 convrot weights load directly; see [INT8 convrot](./int8_convrot.md) for backend requirements.

## Examples

### Fibo 2.0 Dev

Dev supports both text-to-image generation and reference-image editing.

```
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -p "a lovely cat holding a sign says 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v  --offload-to-cpu
```

<img src="../assets/fibo2/t2i.png" />

```
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_dev_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 5.0 --sampling-method euler -v  --offload-to-cpu
```

<img src="../assets/fibo2/dev_edit.png" />

### Fibo 2.0 Edit Turbo

Edit Turbo is distilled for reference-image editing in 4 steps with CFG 1.

```
.\bin\Release\sd-cli.exe --diffusion-model ..\models\diffusion_models\fibo2_edit_turbo_int8_convrot.safetensors --llm ..\models\text_encoders\Qwen3-VL-4B-Instruct-Q4_K_M.gguf --llm_vision ..\models\text_encoders\Qwen3-VL-4B-Instruct-mmproj-BF16.gguf --vae ..\models\vae\flux2_ae.safetensors -r ..\assets\flux\flux1-dev-q8_0.png -p "change 'flux.cpp' to 'fibo2.cpp'" --cfg-scale 1 --steps 4 --sampling-method euler -v  --offload-to-cpu
```

The BF16 files accept the same options. Use dimensions divisible by 16. Repeat `-r` to use multiple reference images; instructions can refer to `<image_1>`, `<image_2>`, etc. See [Image Editing](./edit.md) for reference-image preprocessing options. Separate GGUF text encoders need their vision projector passed with `--llm_vision` for editing.

The automatic `fibo2` reference preset combines `resize_single_ref_to_target=true`, `vae_size_buckets=true`, `vae_center_crop=true`, and `vlm_use_vae_input=true`. A single reference is scaled to cover the output dimensions and center-cropped. Multiple references use dimensions divisible by 16, chosen within ±10% of one megapixel to minimize cropping for each image's aspect ratio; `vae_input_max_pixels` overrides that target area. The VAE and vision encoder receive the same crops, with smaller copies used by the vision encoder. These are generic reference-image options and can be overridden individually: for example, `--ref-image-args vae_center_crop=false` uses direct resizing, while `resize_before_vae=false` skips this automatic crop and resize step entirely.

The vision encoder defaults to `vlm_resize_mode=longest_side,vlm_max_size=768`. Override these with `--ref-image-args`, for example `vlm_max_size=512`, or use `vlm_resize_mode=none` to skip size-based scaling. Vision inputs are still aligned to the encoder's patch grid.

Plain prompts and structured JSON captions are accepted. This integration uses the caption-only text-rendering path (`render_text_images=False`); it does not generate auxiliary glyph images or expand prompts with Bria VGL. Native Fibo mask preprocessing is not connected to `--mask`.