最近笔者在折腾smolVLM的时候，在使用官方提供的如下加载代码时：

processor = AutoProcessor.from_pretrained("HuggingFaceTB/SmolVLM-256M-Instruct")
model = AutoModelForVision2Seq.from_pretrained(
    "HuggingFaceTB/SmolVLM-256M-Instruct",
    torch_dtype=torch.bfloat16,
    _attn_implementation="flash_attention_2" if DEVICE == "cuda" else "eager",
).to(DEVICE)

 flash attention 给出了以下的提示：

You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.

最初以为是flash attention 2的安装问题，使用了Flash-attention 安装指南-知乎中提供的测试代码，进行测试，发现安装没有问题

#测试代码
import torch
from flash_attn import flash_attn_func
import time

def test_flash_attention():
    # 设置随机种子以确保结果可重现
    torch.manual_seed(0)
    
    # 生成随机测试数据
    batch_size = 2
    seq_len = 1024
    num_heads = 8
    head_dim = 64
    
    # 创建随机查询、键和值张量
    q = torch.randn(batch_size, seq_len, num_heads, head_dim, device='cuda', dtype=torch.float16)
    k = torch.randn(batch_size, seq_len, num_heads, head_dim, device='cuda', dtype=torch.float16)
    v = torch.randn(batch_size, seq_len, num_heads, head_dim, device='cuda', dtype=torch.float16)
    
    try:
        # 测试 Flash Attention
        start_time = time.time()
        output = flash_attn_func(q, k, v, causal=True)
        flash_time = time.time() - start_time
        
        print("Flash Attention 测试成功!")
        print(f"输出张量形状: {output.shape}")
        print(f"运行时间: {flash_time:.4f} 秒")
        print("\n张量设备位置:", output.device)
        print("张量数据类型:", output.dtype)
        
        return True
        
    except Exception as e:
        print("Flash Attention 测试失败")
        print("错误信息:", str(e))
        return False

if __name__ == "__main__":
    if torch.cuda.is_available():
        print("CUDA 可用")
        print("GPU:", torch.cuda.get_device_name(0))
        test_flash_attention()
    else:
        print("错误: 需要 CUDA 支持才能运行 Flash Attention")

对官方提供的加载代码进行如下修改，依旧报错：

#将末尾的
.to(DEVICE)
#显式修改为
to("cuda")

最终解决方法：

在加载函数中强制将模型加载到GPU

device_map="cuda" 

修改后的完整函数：

processor = AutoProcessor.from_pretrained("HuggingFaceTB/SmolVLM-256M-Instruct")
model = AutoModelForVision2Seq.from_pretrained(
    "HuggingFaceTB/SmolVLM-256M-Instruct",
    torch_dtype=torch.bfloat16,
    _attn_implementation="flash_attention_2" if DEVICE == "cuda" else "eager",
    device_map="cuda" ,
).to(DEVICE)

至此，flash attention不再提示加载问题。