File size: 1,485 Bytes
171f557 | 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 | 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/"),
)
pipe.dit = pipe.enable_lora_hot_loading(pipe.dit) # Important!
template = TemplatePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[ModelConfig(model_id="DiffSynth-Studio/TreeAdapter-KleinBase4B", origin_file_pattern="iNaturalist/")],
)
name = "Glareola pratincola"
prompt = "A small bird with a long tail and short wings stands on sandy ground. Its plumage is light brown above, white below, with a dark collar around its neck. The background is a blurred expanse of sand."
image = template(
pipe,
seed=0, cfg_scale=4, num_inference_steps=40,
template_inputs = [{"name": name, "prompt": prompt}],
negative_template_inputs = [{"name": name}],
)
image.save("image.jpg")
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