Tokenizer configuration – MLX

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Summary

The issue at hand is related to incorrect tokenization when loading a model on MLX and using its tokenizer. This is due to an incorrect regex pattern in the tokenizer configuration. To resolve this, it’s essential to set the fix_mistral_regex flag to True when loading the tokenizer.

Root Cause

The root cause of this issue is:

  • Incorrect regex pattern in the tokenizer configuration
  • Failure to set the fix_mistral_regex flag to True when loading the tokenizer
  • Insufficient understanding of the tokenizer’s configuration options

Why This Happens in Real Systems

This issue occurs in real systems due to:

  • Complexity of model and tokenizer configurations
  • Lack of documentation or unclear documentation on configuration options
  • Inadequate testing of model and tokenizer configurations

Real-World Impact

The real-world impact of this issue includes:

  • Incorrect tokenization leading to poor model performance
  • Inaccurate results or unexpected behavior from the model
  • Wasted resources due to inefficient debugging and trial-and-error approaches

Example or Code

from mlx_lm import load, generate

out = load("mlx-community/translategemma-12b-it-4bit", fix_mistral_regex=True)

if len(out) == 2:
    model, tokenizer = out
else:
    model, tokenizer, struct = out

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]

prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

How Senior Engineers Fix It

Senior engineers fix this issue by:

  • Carefully reviewing the model and tokenizer configurations
  • Setting the fix_mistral_regex flag to True when loading the tokenizer
  • Thoroughly testing the model and tokenizer configurations

Why Juniors Miss It

Junior engineers may miss this issue due to:

  • Lack of experience with complex model and tokenizer configurations
  • Insufficient understanding of regex patterns and their impact on tokenization
  • Inadequate attention to detail when reviewing configuration options and documentation