LSS

模型介绍

本模型依托魔搭社区（ModelScope）AIGC专区模型训练环境与算力完成训练。

• 模型类型：LoRA
• 基础模型：openmoss/MOSS-Image-SFT
• 训练代码：DiffSynth-Studio
• 训练数据量：36
• 总训练步数：6000
• 开源协议：Apache-2.0

推理代码

安装 DiffSynth-Studio：

pip install diffsynth

开始推理：

from diffsynth.pipelines.moss_image import MOSSImagePipeline, ModelConfig
import torch

pipe = MOSSImagePipeline.from_pretrained(
    torch_dtype=torch.bfloat16,
    device="cuda",
    model_configs=[
        ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
        ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="text_encoder/model*.safetensors"),
        ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="vae/diffusion_pytorch_model.safetensors", computation_dtype=torch.float32),
    ],
    tokenizer_config=ModelConfig(model_id="openmoss/MOSS-Image-SFT", origin_file_pattern="tokenizer/"),
)
pipe.load_lora(pipe.dit, ModelConfig(model_id="gzj134/LSS3", origin_file_pattern="LSS3_c1-st6000.safetensors"))

prompt = "a cat"
image = pipe(prompt, height=1024, width=1024, seed=0, num_inference_steps=50, cfg_scale=3.0)
image.save("image.jpg")