Hi I am also facing the same issue with pytorch 0.3.0 and I am also feeding a FloatTensor to squezeNet, I have attached the source code to the message.
import torchvision
from torchvision import transforms
import torch 
import torch.nn as nn
from PIL import Image
import requests
import io

squeeze = torchvision.models.squeezenet1_1(pretrained=True)

IMG_URL = 'https://s3.amazonaws.com/outcome-blog/wp-content/uploads/2017/02/25192225/cat.jpg'
response = requests.get(IMG_URL)
img_pil = Image.open(io.BytesIO(response.content))


normalize = transforms.Normalize(
   mean=[0.485, 0.456, 0.406],
   std=[0.229, 0.224, 0.225]
)
preprocess = transforms.Compose([
   transforms.Resize(256),
   transforms.CenterCrop(224),
   transforms.ToTensor(),
   normalize
])
    
img_tensor = preprocess(img_pil)
data = img_tensor.unsqueeze(0)
squeeze(data)