Instead of reading in the tokenized input text, our model reads raw utf-8 bytes. For English text in the ASCII range, this is equivalent to processing characters as individual tokens. Non-ASCII characters (e.g. accented characters, or non-Latin scripts) are typically two or three utf-8 bytes. We use a standard “transformer decoder” (a stack of transformer layers with a causal attention mask) to process the sequence $x_{0:i-1}$ and predict the following byte $x_i$. The model's prediction is an estimate of the probability distribution over all possible 256 byte values. Our input byte embedding matrix has dimensionality 256. 
 Question: How many characters are accepted as input of the language model?
input byte embedding matrix has dimensionality 256