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# FLUX.1-dev

[FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) is a 12B parameter text-to-image diffusion transformer from Black Forest Labs, trained with flow matching. It produces high-fidelity images and is designed for non-commercial research and development use.

> **Info**
>
> |                  |                                                               |
> | ---------------- | ------------------------------------------------------------- |
> | **Task**         | Text-to-Image                                                 |
> | **Architecture** | DiT (Flow Matching)                                           |
> | **Parameters**   | 12B                                                           |
> | **HF Org**       | [black-forest-labs](https://huggingface.co/black-forest-labs) |

## Available Models

* **FLUX.1-dev**: 12B parameters

## Task

* Text-to-Image (T2I)

## Example HF Models

| Model      | HF ID                                                                                 |
| ---------- | ------------------------------------------------------------------------------------- |
| FLUX.1-dev | [`black-forest-labs/FLUX.1-dev`](https://huggingface.co/black-forest-labs/FLUX.1-dev) |

## Example Recipes

| Recipe                                                                                                                    | Description                               |
| ------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------- |
| [flux\_t2i\_flow.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/diffusion/finetune/flux_t2i_flow.yaml) | Fine-tune — FLUX.1-dev with flow matching |
| [flux\_t2i\_flow.yaml](https://github.com/NVIDIA-NeMo/Automodel/blob/main/examples/diffusion/pretrain/flux_t2i_flow.yaml) | Pretrain — FLUX.1-dev with flow matching  |

## Try with NeMo AutoModel

**1. Install** ([full instructions](/get-started/installation)):

```bash
pip install "nemo-automodel[diffusion,diffusion-media]"
```

**2. Clone the repo** to get the example recipes:

```bash
git clone https://github.com/NVIDIA-NeMo/Automodel.git
cd Automodel
```

**3. Run the recipe** from inside the repo:

```bash
torchrun --nproc-per-node=8 \
  examples/diffusion/finetune/finetune.py \
  -c examples/diffusion/finetune/flux_t2i_flow.yaml
```

#### Run with Docker

**1. Pull the container** and mount a checkpoint directory:

```bash
docker run --gpus all -it --rm \
  --shm-size=8g \
  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
  nvcr.io/nvidia/nemo-automodel:26.06.00
```

**2.** Navigate to the AutoModel directory (where the recipes are):

```bash
cd /opt/Automodel
```

**3. Install media dependencies** (not installed in the container by default):

```bash
uv pip install ".[diffusion-media]"
```

**4. Run the recipe**:

```bash
torchrun --nproc-per-node=8 \
  examples/diffusion/finetune/finetune.py \
  -c examples/diffusion/finetune/flux_t2i_flow.yaml
```

See the [Installation Guide](/get-started/installation) and [Diffusion Fine-Tuning Guide](/recipes-e2e-examples/diffusion-fine-tuning).

## Training

See the [Diffusion Training and Fine-Tuning Guide](/recipes-e2e-examples/diffusion-fine-tuning) and [Dataset Preparation](/datasets/diffusion-dataset).

## Hugging Face Model Cards

* [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev)