You can change the tokenizer's vocabulary:

tokenizer.add_tokens(["asadaf", "sdfsaf"])
model.resize_token_embeddings(len(tokenizer)) # change input embeddings size
input_text = "This is asadaf and sdfsaf"
print(tokenizer(input_text))

As a result, asadaf and sdfsaf would be tokenized as unique words.