You can build your own dataset by using Dataset Class

class my dataset (Dataset):

You have to over ride two function -  len() and getitem()
Now,
len() returns the length of the dataset, which you need, so that you can iterate over it getitem() returns the item
class myDataset(Dataset):
   def __init__(self):
      self.load_files = []
      load_file = pd.csv(filename)
      load_files.append(load_file)
  
   def __len__(self):
      return len(self.load_files)
   
   def __getitem__(self,idx):
      sample = self.load_files[idx]
      # type of sample would be of dataframe, we need to convert it into Tensor and then return
     return sample 

It is not necessary to have labels. Only, thing is that you need to have tensor output from getitem() and when you iterate over dataset, extract the data carefully. And override those two functions
Check this :https://pytorch.org/tutorials/beginner/data_loading_tutorial.html
It has explained it beautifully