Model CoverageDiffusion Models

FLUX.1-dev

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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.

TaskText-to-Image
ArchitectureDiT (Flow Matching)
Parameters12B
HF Orgblack-forest-labs

Available Models

  • FLUX.1-dev: 12B parameters

Task

  • Text-to-Image (T2I)

Example HF Models

ModelHF ID
FLUX.1-devblack-forest-labs/FLUX.1-dev

Example Recipes

RecipeDescription
flux_t2i_flow.yamlFine-tune — FLUX.1-dev with flow matching
flux_t2i_flow.yamlPretrain — FLUX.1-dev with flow matching

Try with NeMo AutoModel

1. Install (full instructions):

$pip install nemo-automodel

2. Clone the repo to get the example recipes:

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

3. Run the recipe from inside the repo:

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

1. Pull the container and mount a checkpoint directory:

$docker run --gpus all -it --rm \
>  --shm-size=8g \
>  -v $(pwd)/checkpoints:/opt/Automodel/checkpoints \
>  nvcr.io/nvidia/nemo-automodel:26.04.00

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

$cd /opt/Automodel

3. Run the recipe:

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

See the Installation Guide and Diffusion Fine-Tuning Guide.

Training

See the Diffusion Training and Fine-Tuning Guide and Dataset Preparation.

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