Jordan Legg
working
ed8e391
raw
history blame contribute delete
772 Bytes
from transformers import T5TokenizerFast
# Initialize the tokenizer
tokenizer = T5TokenizerFast.from_pretrained("google/t5-v1_1-xxl", legacy=False)
# Your specific token IDs
token_ids = [3, 23, 31, 51, 3, 12775, 3768, 5, 1]
# Decode the full sequence
full_text = tokenizer.decode(token_ids, skip_special_tokens=True)
print("\nFull decoded text:", full_text)
# Decode each token individually and print its text value
for token_id in token_ids:
# Decode each token without skipping special tokens
token_text = tokenizer.decode([token_id], skip_special_tokens=False)
print(f"Decoded token {token_id}: {token_text}")
# Convert token ID 3 to its token string
token_3_name = tokenizer.convert_ids_to_tokens(3)
print(f"Token ID 3 corresponds to: {token_3_name}")