#!/bin/env python | |
""" | |
According to model, | |
vocab_size: 32128 | |
But it actually caps out at 32099 | |
""" | |
from transformers import T5Tokenizer,T5EncoderModel | |
import torch | |
import charade | |
T="mcmonkey/google_t5-v1_1-xxl_encoderonly" | |
tokenizer = T5Tokenizer.from_pretrained(T) | |
startword= tokenizer.convert_ids_to_tokens(3) | |
#print (startword) | |
# id should be a numeral | |
def print_token_from_id(id): | |
decoded_tokens = tokenizer.convert_ids_to_tokens(id) | |
print(decoded_tokens+" : " + str(id)) | |
# print if it has the marker indicating it is a standalone word, | |
# not just a building block | |
def print_if_word(id): | |
decoded_tokens = tokenizer.convert_ids_to_tokens(id) | |
if decoded_tokens.startswith(startword): | |
print(decoded_tokens[1:] +" : " + str(id)) | |
# standalone word, AND doesnt have any foreign non-ascii7 chars | |
def print_if_asciiword(id): | |
decoded_tokens = tokenizer.convert_ids_to_tokens(id) | |
if decoded_tokens.startswith(startword): | |
aword=decoded_tokens[1:] | |
if len(aword) <1: | |
return | |
estr=str(aword.encode()) | |
if '\\x' in estr: | |
return | |
print(aword +" : " , id) | |
for id in range(4,32099): | |
#print_token_from_id(id) | |
#print_if_word(id) | |
print_if_asciiword(id) | |