Buckets:
| """The canonical ByT5 byte table (fixed, no vocab files). | |
| Stock google/byt5 tokenizers map UTF-8 byte b to id b+3 and append | |
| EOS(1); pad=0, unk=2. Ids are NOT raw byte values — feeding text.bytes | |
| directly produces silent garbage on real models. | |
| """ | |
| from __future__ import annotations | |
| BYTE_OFFSET = 3 | |
| PAD_ID = 0 | |
| EOS_ID = 1 | |
| UNK_ID = 2 | |
| def encode(text: str) -> list[int]: | |
| """Canonical byte-level tokenization (byte+3 table, trailing EOS).""" | |
| return [b + BYTE_OFFSET for b in text.encode("utf-8")] + [EOS_ID] | |
| def decode(token_ids: list[int]) -> str: | |
| """Token ids -> text; stops at EOS, maps id-3 back to a byte.""" | |
| out = bytearray() | |
| for token in token_ids: | |
| if token == EOS_ID: | |
| break | |
| if token in (PAD_ID, UNK_ID): | |
| continue | |
| out.append((token - BYTE_OFFSET) % 256) | |
| return out.decode("utf-8", errors="replace") | |
Xet Storage Details
- Size:
- 884 Bytes
- Xet hash:
- accd33d6d416f737b80b69fc5b4ba27913db456918ba1e09b400d3c42eb20a69
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.