Tokenizer Configuration Files

The tokenizer_config.json and tokenizer.json files serve different purposes in the tokenization process of the Llama3 language model.

Let's clarify the difference between the two and how they interact:

This file contains the configuration settings for the tokenizer
It defines the behaviour and properties of the tokenizer, such as the special tokens, maximum sequence length, and input tensor names.
The tokenizer_config.json file specifies how the tokenizer should handle and interpret the input text during the tokenization process.
It includes settings like the beginning-of-sequence (BOS) token, end-of-sequence (EOS) token, and whether to clean up extra spaces during tokenization.
The tokenizer_config.json file also defines the mapping between special token IDs and their corresponding token content in the "added_tokens_decoder" section.

This file contains the actual vocabulary and mappings used by the tokenizer to convert input text into token IDs.
It defines the mapping between each word, subword, or character in the vocabulary and its corresponding unique token ID.
The tokenizer.json file is used during the tokenization process to look up the token IDs for each word or subword in the input text.
It is a crucial component of the tokenizer and is loaded by the tokenizer implementation to perform the actual tokenization.

The tokenizer_config.json file provides the configuration settings for the tokenizer, specifying how it should behave and handle special tokens.
The tokenizer.json file contains the actual vocabulary and mappings used by the tokenizer to convert input text into token IDs.
During the tokenization process, the tokenizer implementation loads both files:
- It uses the tokenizer_config.json file to configure its behavior and special token handling.
- It uses the tokenizer.json file to look up the token IDs for each word or subword in the input text.
The tokenizer applies the configuration settings from tokenizer_config.json while utilizing the vocabulary and mappings from tokenizer.json to perform the tokenization.

Last updated 1 year ago

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The tokenizer_config.json and tokenizer.json files serve different purposes in the tokenization process of the Llama3 language model.

Let's clarify the difference between the two and how they interact:

This file contains the configuration settings for the tokenizer
It defines the behaviour and properties of the tokenizer, such as the special tokens, maximum sequence length, and input tensor names.
The tokenizer_config.json file specifies how the tokenizer should handle and interpret the input text during the tokenization process.
It includes settings like the beginning-of-sequence (BOS) token, end-of-sequence (EOS) token, and whether to clean up extra spaces during tokenization.
The tokenizer_config.json file also defines the mapping between special token IDs and their corresponding token content in the "added_tokens_decoder" section.

This file contains the actual vocabulary and mappings used by the tokenizer to convert input text into token IDs.
It defines the mapping between each word, subword, or character in the vocabulary and its corresponding unique token ID.
The tokenizer.json file is used during the tokenization process to look up the token IDs for each word or subword in the input text.
It is a crucial component of the tokenizer and is loaded by the tokenizer implementation to perform the actual tokenization.

The tokenizer_config.json file provides the configuration settings for the tokenizer, specifying how it should behave and handle special tokens.
The tokenizer.json file contains the actual vocabulary and mappings used by the tokenizer to convert input text into token IDs.
During the tokenization process, the tokenizer implementation loads both files:
- It uses the tokenizer_config.json file to configure its behavior and special token handling.
- It uses the tokenizer.json file to look up the token IDs for each word or subword in the input text.
The tokenizer applies the configuration settings from tokenizer_config.json while utilizing the vocabulary and mappings from tokenizer.json to perform the tokenization.

Last updated 1 year ago

Was this helpful?