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Artiprocher
2026-04-16 20:24:22 +08:00
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examples/flux2/model_training/validate_full/Template-KleinBase4B-Inpaint.py Normal file
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from diffsynth.diffusion.template import TemplatePipeline
from diffsynth.pipelines.flux2_image import Flux2ImagePipeline, ModelConfig
from diffsynth.core import load_state_dict
import torch
from modelscope import dataset_snapshot_download
from PIL import Image
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-Inpaint")],
)
state_dict = load_state_dict("./models/train/Template-KleinBase4B-Inpaint_full/epoch-1.safetensors", torch_dtype=torch.bfloat16)
template.models[0].load_state_dict(state_dict)
dataset_snapshot_download(
"DiffSynth-Studio/examples_in_diffsynth",
allow_file_pattern=["templates/*"],
local_dir="data/examples",
)
image = template(
pipe,
prompt="An orange cat is sitting on a stone.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs = [{
"image": Image.open("data/examples/templates/image_reference.jpg"),
"mask": Image.open("data/examples/templates/image_mask_1.jpg"),
"force_inpaint": True,
}],
negative_template_inputs = [{
"image": Image.open("data/examples/templates/image_reference.jpg"),
"mask": Image.open("data/examples/templates/image_mask_1.jpg"),
}],
)
image.save("image_Inpaint_1.jpg")
image = template(
pipe,
prompt="A cat wearing sunglasses is sitting on a stone.",
seed=0, cfg_scale=4, num_inference_steps=50,
template_inputs = [{
"image": Image.open("data/examples/templates/image_reference.jpg"),
"mask": Image.open("data/examples/templates/image_mask_2.jpg"),
}],
negative_template_inputs = [{
"image": Image.open("data/examples/templates/image_reference.jpg"),
"mask": Image.open("data/examples/templates/image_mask_2.jpg"),
}],
)
image.save("image_Inpaint_2.jpg")