报错

Error loading model: Error(s) in loading state_dict for xxxAnythingV2:
        Missing key(s) in state_dict: "pretrained.cls_token", "pretrained.pos_embed", "pretrained.mask_token", "pretrained.patch_embed.proj.weight", "pretrained.patch_embed.proj.bias", "pretrained.blocks.0.norm1.weight", "pretrained.blocks.0.norm1.bias", "pretrained.blocks.0.attn.qkv.weight", "pretrained.blocks.0.attn.qkv.bias", "pretrained.blocks.0.attn.proj.weight", "pretrained.blocks.0.attn.proj.bias", "pretrained.blocks.0.ls1.gamma", "pretrained.blocks.0.norm2.weight", "pretrained.blocks.0.norm2.bias", "pretrained.blocks.0.mlp.fc1.weight", "pretrained.blocks.0.mlp.fc1.bias", "pretrained.blocks.0.mlp.fc2.weight", "pretrained.blocks.0.mlp.fc2.bias", "pretrained.blocks.0.ls2.gamma", "pretrained.blocks.1.norm1.weight", "pretrained.blocks.1.norm1.bias", "pretrained.blocks.1.attn.qkv.weight", "pretrained.blocks.1.attn.qkv.bias", "pretrained.blocks.1.attn.proj.weight", "pretrained.blocks.1.attn.proj.bias", "pretrained.blocks.1.ls1.gamma", "pretrained.blocks.1.norm2.weight", "pretrained.blocks.1.norm2.bias", "pretrained.blocks.1.mlp.fc1.weight", "pretrained.blocks.1.mlp.fc1.bias", "pretrained.blocks.1.mlp.fc2.weight", "pretrained.blocks.1.mlp.fc2.bias", "pretrained.blocks.1.ls2.gamma", "pretrained.blocks.2.norm1.weight", "pretrained.blocks.2.norm1.bias", "pretrained.blocks.2.attn.qkv.weight", "pretrained.blocks.2.attn.qkv.bias", "pretrained.blocks.2.attn.proj.weight", "pretrained.blocks.2.attn.proj.bias", "pretrained.blocks.2.ls1.gamma", "pretrained.blocks.2.norm2.weight", "pretrained.blocks.2.norm2.bias", "pretrained.blocks.2.mlp.fc1.weight", "pretrained.blocks.2.mlp.fc1.bias", "pretrained.blocks.2.mlp.fc2.weight", "pretrained.blocks.2.mlp.fc2.bias", "pretrained.blocks.2.ls2.gamma", "pretrained.blocks.3.norm1.weight", "pretrained.blocks.3.norm1.bias", "pretrained.blocks.3.attn.qkv.weight", "pretrained.blocks.3.attn.qkv.bias", "pretrained.blocks.3.attn.proj.weight", "pretrained.blocks.3.attn.proj.bias", "pretrained.blocks.3.ls1.gamma", "pretrained.blocks.3.norm2.weight", "pretrained.blocks.3.norm2.bias", "pretrained.blocks.3.mlp.fc1.weight", "pretrained.blocks.3.mlp.fc1.bias", "pretrained.blocks.3.mlp.fc2.weight", "pretrained.blocks.3.mlp.fc2.bias", "pretrained.blocks.3.ls2.gamma", "pretrained.blocks.4.norm1.weight", "pretrained.blocks.4.norm1.bias", "pretrained.blocks.4.attn.qkv.weight", "pretrained.blocks.4.attn.qkv.bias", "pretrained.blocks.4.attn.proj.weight", "pretrained.blocks.4.attn.proj.bias", "pretrained.blocks.4.ls1.gamma", "pretrained.blocks.4.norm2.weight", "pretrained.blocks.4.norm2.bias", "pretrained.blocks.4.mlp.fc1.weight", "pretrained.blocks.4.mlp.fc1.bias", "pretrained.blocks.4.mlp.fc2.weight", "pretrained.blocks.4.mlp.fc2.bias", "pretrained.blocks.4.ls2.gamma", "pretrained.blocks.5.norm1.weight", "pretrained.blocks.5.norm1.bias", "pretrained.blocks.5.attn.qkv.weight", "pretrained.blocks.5.attn.qkv.bias", "pretrained.blocks.5.attn.proj.weight", "pretrained.blocks.5.attn.proj.bias", "pretrained.blocks.5.ls1.gamma", "pretrained.blocks.5.norm2.weight", "pretrained.blocks.5.norm2.bias", "pretrained.blocks.5.mlp.fc1.weight", "pretrained.blocks.5.mlp.fc1.bias", "pretrained.blocks.5.mlp.fc2.weight", "pretrained.blocks.5.mlp.fc2.bias", "pretrained.blocks.5.ls2.gamma", "pretrained.blocks.6.norm1.weight", "pretrained.blocks.6.norm1.bias", "pretrained.blocks.6.attn.qkv.weight", "pretrained.blocks.6.attn.qkv.bias", "pretrained.blocks.6.attn.proj.weight", "pretrained.blocks.6.attn.proj.bias", "pretrained.blocks.6.ls1.gamma", "pretrained.blocks.6.norm2.weight", "pretrained.blocks.6.norm2.bias", "pretrained.blocks.6.mlp.fc1.weight", "pretrained.blocks.6.mlp.fc1.bias", "pretrained.blocks.6.mlp.fc2.weight", "pretrained.blocks.6.mlp.fc2.bias", "pretrained.blocks.6.ls2.gamma", "pretrained.blocks.7.norm1.weight", "pretrained.blocks.7.norm1.bias", "pretrained.blocks.7.attn.qkv.weight", "pretrained.blocks.7.attn.qkv.bias", "pretrained.blocks.7.attn.proj.weight", "pretrained.blocks.7.attn.proj.bias", "pretrained.blocks.7.ls1.gamma", "pretrained.blocks.7.norm2.weight", "pretrained.blocks.7.norm2.bias", "pretrained.blocks.7.mlp.fc1.weight", "pretrained.blocks.7.mlp.fc1.bias", "pretrained.blocks.7.mlp.fc2.weight", "pretrained.blocks.7.mlp.fc2.bias", "pretrained.blocks.7.ls2.gamma", "pretrained.blocks.8.norm1.weight", "pretrained.blocks.8.norm1.bias", "pretrained.blocks.8.attn.qkv.weight", "pretrained.blocks.8.attn.qkv.bias", "pretrained.blocks.8.attn.proj.weight", "pretrained.blocks.8.attn.proj.bias", "pretrained.blocks.8.ls1.gamma", "pretrained.blocks.8.norm2.weight", "pretrained.blocks.8.norm2.bias", "pretrained.blocks.8.mlp.fc1.weight", "pretrained.blocks.8.mlp.fc1.bias", "pretrained.blocks.8.mlp.fc2.weight", "pretrained.blocks.8.mlp.fc2.bias", "pretrained.blocks.8.ls2.gamma", "pretrained.blocks.9.norm1.weight", "pretrained.blocks.9.norm1.bias", "pretrained.blocks.9.attn.qkv.weight", "pretrained.blocks.9.attn.qkv.bias", "pretrained.blocks.9.attn.proj.weight", "pretrained.blocks.9.attn.proj.bias", "pretrained.blocks.9.ls1.gamma", "pretrained.blocks.9.norm2.weight", "pretrained.blocks.9.norm2.bias", "pretrained.blocks.9.mlp.fc1.weight", "pretrained.blocks.9.mlp.fc1.bias", "pretrained.blocks.9.mlp.fc2.weight", "pretrained.blocks.9.mlp.fc2.bias", "pretrained.blocks.9.ls2.gamma", "pretrained.blocks.10.norm1.weight", "pretrained.blocks.10.norm1.bias", "pretrained.blocks.10.attn.qkv.weight", "pretrained.blocks.10.attn.qkv.bias", "pretrained.blocks.10.attn.proj.weight", "pretrained.blocks.10.attn.proj.bias", "pretrained.blocks.10.ls1.gamma", "pretrained.blocks.10.norm2.weight", "pretrained.blocks.10.norm2.bias", "pretrained.blocks.10.mlp.fc1.weight", "pretrained.blocks.10.mlp.fc1.bias", "pretrained.blocks.10.mlp.fc2.weight", "pretrained.blocks.10.mlp.fc2.bias", "pretrained.blocks.10.ls2.gamma", "pretrained.blocks.11.norm1.weight", "pretrained.blocks.11.norm1.bias", "pretrained.blocks.11.attn.qkv.weight", "pretrained.blocks.11.attn.qkv.bias", "pretrained.blocks.11.attn.proj.weight", "pretrained.blocks.11.attn.proj.bias", "pretrained.blocks.11.ls1.gamma", "pretrained.blocks.11.norm2.weight", "pretrained.blocks.11.norm2.bias", "pretrained.blocks.11.mlp.fc1.weight", "pretrained.blocks.11.mlp.fc1.bias", "pretrained.blocks.11.mlp.fc2.weight", "pretrained.blocks.11.mlp.fc2.bias", "pretrained.blocks.11.ls2.gamma", "pretrained.norm.weight", "pretrained.norm.bias", "xxx_head.projects.0.weight", "xxx_head.projects.0.bias", "xxx_head.projects.1.weight", "xxx_head.projects.1.bias", "xxx_head.projects.2.weight", "xxx_head.projects.2.bias", "xxx_head.projects.3.weight", "xxx_head.projects.3.bias", "xxx_head.resize_layers.0.weight", "xxx_head.resize_layers.0.bias", "xxx_head.resize_layers.1.weight", "xxx_head.resize_layers.1.bias", "xxx_head.resize_layers.3.weight", "xxx_head.resize_layers.3.bias", "xxx_head.scratch.layer1_rn.weight", "xxx_head.scratch.layer2_rn.weight", "xxx_head.scratch.layer3_rn.weight", "xxx_head.scratch.layer4_rn.weight", "xxx_head.scratch.refinenet1.out_conv.weight", "xxx_head.scratch.refinenet1.out_conv.bias", "xxx_head.scratch.refinenet1.resConfUnit1.conv1.weight", "xxx_head.scratch.refinenet1.resConfUnit1.conv1.bias", "xxx_head.scratch.refinenet1.resConfUnit1.conv2.weight", "xxx_head.scratch.refinenet1.resConfUnit1.conv2.bias", "xxx_head.scratch.refinenet1.resConfUnit2.conv1.weight", "xxx_head.scratch.refinenet1.resConfUnit2.conv1.bias", "xxx_head.scratch.refinenet1.resConfUnit2.conv2.weight", "xxx_head.scratch.refinenet1.resConfUnit2.conv2.bias", "xxx_head.scratch.refinenet2.out_conv.weight", "xxx_head.scratch.refinenet2.out_conv.bias", "xxx_head.scratch.refinenet2.resConfUnit1.conv1.weight", "xxx_head.scratch.refinenet2.resConfUnit1.conv1.bias", "xxx_head.scratch.refinenet2.resConfUnit1.conv2.weight", "xxx_head.scratch.refinenet2.resConfUnit1.conv2.bias", "xxx_head.scratch.refinenet2.resConfUnit2.conv1.weight", "xxx_head.scratch.refinenet2.resConfUnit2.conv1.bias", "xxx_head.scratch.refinenet2.resConfUnit2.conv2.weight", "xxx_head.scratch.refinenet2.resConfUnit2.conv2.bias", "xxx_head.scratch.refinenet3.out_conv.weight", "xxx_head.scratch.refinenet3.out_conv.bias", "xxx_head.scratch.refinenet3.resConfUnit1.conv1.weight", "xxx_head.scratch.refinenet3.resConfUnit1.conv1.bias", "xxx_head.scratch.refinenet3.resConfUnit1.conv2.weight", "xxx_head.scratch.refinenet3.resConfUnit1.conv2.bias", "xxx_head.scratch.refinenet3.resConfUnit2.conv1.weight", "xxx_head.scratch.refinenet3.resConfUnit2.conv1.bias", "xxx_head.scratch.refinenet3.resConfUnit2.conv2.weight", "xxx_head.scratch.refinenet3.resConfUnit2.conv2.bias", "xxx_head.scratch.refinenet4.out_conv.weight", "xxx_head.scratch.refinenet4.out_conv.bias", "xxx_head.scratch.refinenet4.resConfUnit1.conv1.weight", "xxx_head.scratch.refinenet4.resConfUnit1.conv1.bias", "xxx_head.scratch.refinenet4.resConfUnit1.conv2.weight", "xxx_head.scratch.refinenet4.resConfUnit1.conv2.bias", "xxx_head.scratch.refinenet4.resConfUnit2.conv1.weight", "xxx_head.scratch.refinenet4.resConfUnit2.conv1.bias", "xxx_head.scratch.refinenet4.resConfUnit2.conv2.weight", "xxx_head.scratch.refinenet4.resConfUnit2.conv2.bias", "xxx_head.scratch.output_conv1.weight", "xxx_head.scratch.output_conv1.bias", "xxx_head.scratch.output_conv2.0.weight", "xxx_head.scratch.output_conv2.0.bias", "xxx_head.scratch.output_conv2.2.weight", "xxx_head.scratch.output_conv2.2.bias".
        Unexpected key(s) in state_dict: "date", "version", "license", "docs", "epoch", "best_fitness", "model", "ema", "updates", "optimizer", "train_args", "train_metrics", "train_results", "multimodal_config", "modality".

加载的 .pt 文件是一个完整的 Ultralytics-YOLO 训练检查点（包含 ema, optimizer, train_args 等大量非网络权重字段），而 xxx（你当前代码）只需要“纯权重”。
因此 state_dict 里 缺失 了 xxx 模型所需的键，同时 多余 了 YOLO 专用的键。

解决方案:

在模型加载处 加上 strict=False

model.load_state_dict(torch.load('yolo11n.pt', map_location='cpu'), strict=False)