Hi there, here is a quick way to do this for the last token on a given sentence in PyTorch:
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch
import torch.nn.functional as F

# Load model and tokenizer
model = GPT2LMHeadModel.from_pretrained('gpt2')
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')

# Input example
input_txt = "Hello, my name is Sylvain."
inputs = tokenizer(input_txt, return_tensors='pt')
outputs = model(**inputs)

# If you are not on a source install, replace outputs.logits by outputs[0]
predictions = F.softmax(outputs.logits, dim=-1)

thresh = 1e-2
vocab_size = predictions.shape[-1]

# Predictions has one sentence (index 0) and we look at the last token predicted (-1)
idxs = torch.arange(0, vocab_size)[predictions[0][-1] >= thresh]
print(tokenizer.convert_ids_to_tokens(idxs))