Just following the code (for PyTorch) for the course leads to a small error:
outputs = model(**inputs)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
...

TypeError: forward() got an unexpected keyword argument 'token_type_ids'

I removed the problematic token_type_ids key and it worked:
outputs = model(** { k: inputs[k] for k in ['input_ids', 'attention_mask'] })

But, then, the result is not what we expected:
import torch
from transformers import AutoModelForSequenceClassification

checkpoint = "distilbert-base-uncased-finetuned-sst-2-english"
model = AutoModelForSequenceClassification.from_pretrained(checkpoint)
raw_inputs = [
    "I've been waiting for a HuggingFace course my whole life.", 
    "I hate this so much!",
]
inputs = tokenizer(raw_inputs, padding=True, truncation=True, return_tensors="pt")
outputs = model(**{ k: inputs[k] for k in ['input_ids', 'attention_mask'] })
predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
print(predictions)
-----
tensor([[0.9618, 0.0382],
        [0.9350, 0.0650]], grad_fn=<SoftmaxBackward>)