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---
library_name: transformers
license: apache-2.0
tags:
- tokenizer
- claude3
- t5
---
# claude3 tokenizer: for T5
Vocabulary size: 65103
- relevant special tokens for T5 training added
- post processor updated following t5's tokenizer
usage:
```py
from transformers import AutoTokenizer
tk = AutoTokenizer.from_pretrained('BEE-spoke-data/claude-tokenizer-forT5')
inputs = tk("here are some words", return_tensors="pt")
```
## post processor
```json
"post_processor": {
"type": "TemplateProcessing",
"single": [
{
"Sequence": {
"id": "A",
"type_id": 0
}
},
{
"SpecialToken": {
"id": "</s>",
"type_id": 0
}
}
],
"pair": [
{
"Sequence": {
"id": "A",
"type_id": 0
}
},
{
"SpecialToken": {
"id": "</s>",
"type_id": 0
}
},
{
"Sequence": {
"id": "B",
"type_id": 0
}
},
{
"SpecialToken": {
"id": "</s>",
"type_id": 0
}
}
],
"special_tokens": {
"</s>": {
"id": "</s>",
"ids": [
65001
],
"tokens": [
"</s>"
]
}
}
},
``` |