File size: 7,885 Bytes
8c6a02f 3fb0275 8c6a02f 3eeabf4 8c6a02f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 | ---
license: apache-2.0
---
# Templates - Age Control (FLUX.2-klein-base-4B)
This model is one of the Diffusion Templates series models open-sourced by [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio). It allows direct control over the age of the person in the generated image by inputting the `age` parameter.
* Open-source code: [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
* Technical report: [arXiv](https://arxiv.org/abs/2604.24351)
* Project page: [GitHub](https://modelscope.github.io/diffusion-templates-web/)
* Documentation: [English Version](https://diffsynth-studio-doc.readthedocs.io/en/latest/Diffusion_Templates/Introducing_Diffusion_Templates.html)、[中文版](https://diffsynth-studio-doc.readthedocs.io/zh-cn/latest/Diffusion_Templates/Introducing_Diffusion_Templates.html)
* Online demo: [ModelScope](https://modelscope.cn/studios/DiffSynth-Studio/Diffusion-Templates)
* Models: [ModelScope](https://modelscope.cn/collections/DiffSynth-Studio/KleinBase4B-Templates)、[ModelScope International](https://modelscope.ai/collections/DiffSynth-Studio/KleinBase4B-Templates)、[HuggingFace](https://huggingface.co/collections/DiffSynth-Studio/kleinbase4b-templates)
* Datasets: [ModelScope](https://modelscope.cn/collections/DiffSynth-Studio/ImagePulseV2)、[ModelScope International](https://modelscope.cn/collections/DiffSynth-Studio/ImagePulseV2)、[HuggingFace](https://huggingface.co/collections/DiffSynth-Studio/imagepulsev2)
## Results
> **Prompt:** A portrait of a woman with black hair, wearing a suit.
| Age = 20 | Age = 50 | Age = 80 |
|:---:|:---:|:---:|
|  |  |  |
---
> **Prompt:** A portrait of a man, autumn park background, warm evening sunlight.
| Age = 20 | Age = 50 | Age = 80 |
|:---:|:---:|:---:|
|  |  |  |
---
A fashion portrait of an elegant woman wearing a red silk dress, high fashion photography, soft lighting. A modern minimalist living room with furniture.
| Age = 20 | Age = 50 | Age = 80 |
|:---:|:---:|:---:|
|  |  |  |
## Inference Code
* Install [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)
```
git clone https://github.com/modelscope/DiffSynth-Studio.git
cd DiffSynth-Studio
pip install -e .
```
* Direct inference (requires 40G GPU memory)
```python
from diffsynth.diffusion.template import TemplatePipeline
from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
import torch
pipe = Flux2ImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors"),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
)
template = TemplatePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Age")],
)
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 20}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_20.jpg")
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 50}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_50.jpg")
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 80}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_80.jpg")
```
* Enable lazy loading and memory management, requires 24G GPU memory
```python
from diffsynth.diffusion.template import TemplatePipeline
from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
import torch
vram_config = {
"offload_dtype": "disk",
"offload_device": "disk",
"onload_dtype": torch.float8_e4m3fn,
"onload_device": "cpu",
"preparing_dtype": torch.float8_e4m3fn,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = Flux2ImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-base-4B", origin_file_pattern="transformer/*.safetensors", **vram_config),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="text_encoder/*.safetensors", **vram_config),
ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=ModelConfig(model_id="black-forest-labs/FLUX.2-klein-4B", origin_file_pattern="tokenizer/"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)
template = TemplatePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[ModelConfig(model_id="DiffSynth-Studio/Template-KleinBase4B-Age")],
lazy_loading=True,
)
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 20}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_20.jpg")
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 50}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_50.jpg")
image = template(
pipe,
prompt="A portrait of a woman with black hair, wearing a suit.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs=[{"age": 80}],
negative_template_inputs=[{"age": 45}],
)
image.save(f"image_age_80.jpg")
```
## Training Code
After installing DiffSynth-Studio, use the following script to start training. For more information, please refer to the [DiffSynth-Studio Documentation](https://diffsynth-studio-doc.readthedocs.io/zh-cn/latest/).
```shell
modelscope download --dataset DiffSynth-Studio/diffsynth_example_dataset --include "flux2/Template-KleinBase4B-Age/*" --local_dir ./data/diffsynth_example_dataset
accelerate launch examples/flux2/model_training/train.py \
--dataset_base_path data/diffsynth_example_dataset/flux2/Template-KleinBase4B-Age \
--dataset_metadata_path data/diffsynth_example_dataset/flux2/Template-KleinBase4B-Age/metadata.jsonl \
--extra_inputs "template_inputs" \
--max_pixels 1048576 \
--dataset_repeat 50 \
--model_id_with_origin_paths "black-forest-labs/FLUX.2-klein-4B:text_encoder/*.safetensors,black-forest-labs/FLUX.2-klein-base-4B:transformer/*.safetensors,black-forest-labs/FLUX.2-klein-4B:vae/diffusion_pytorch_model.safetensors" \
--template_model_id_or_path "DiffSynth-Studio/Template-KleinBase4B-Age:" \
--tokenizer_path "black-forest-labs/FLUX.2-klein-4B:tokenizer/" \
--learning_rate 1e-4 \
--num_epochs 2 \
--remove_prefix_in_ckpt "pipe.template_model." \
--output_path "./models/train/Template-KleinBase4B-Age_full" \
--trainable_models "template_model" \
--use_gradient_checkpointing \
--find_unused_parameters
``` |