You can specify the tokenizer with the tokenizer argument and do what is suggested in the error message.
Here is an example based on the documentation 6.
tokenizer = AutoTokenizer.from_pretrained("gpt2")
model = AutoModel.from_pretrained("gpt2")

tokenizer.add_special_tokens({'pad_token': '[PAD]'})
model.resize_token_embeddings(len(tokenizer))

pipe = pipeline('feature-extraction', model=model, tokenizer=tokenizer)

This works for me. Let me know if you have any other questions