transforms/universal/tokenization/tokenization.ipynb

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    "##### **** These pip installs need to be adapted to use the appropriate release level. Alternatively, The venv running the jupyter lab could be pre-configured with a requirement file that includes the right release. Example for transform developers working from git clone:\n",
    "```\n",
    "make venv \n",
    "source venv/bin/activate \n",
    "pip install jupyterlab\n",
    "```"
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    "%%capture\n",
    "## This is here as a reference only\n",
    "# Users and application developers must use the right tag for the latest from pypi\n",
    "!pip install data-prep-toolkit\n",
    "!pip install data-prep-toolkit-transforms[tokenization]"
   ]
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    "##### **** Configure the transform parameters. The set of dictionary keys holding DocIDTransform configuration for values are as follows: \n",
    "| Name | Description|\n",
    "| -----|------------|\n",
    "|tkn_tokenizer | Tokenizer used for tokenization. It also can be a path to a pre-trained tokenizer. By defaut, `hf-internal-testing/llama-tokenizer` from HuggingFace is used |\n",
    "|tkn_tokenizer_args |Arguments for tokenizer. For example, `cache_dir=/tmp/hf,use_auth_token=Your_HF_authentication_token` could be arguments for tokenizer `bigcode/starcoder` from HuggingFace|\n",
    "|tkn_doc_id_column|Column contains document id which values should be unique across dataset|\n",
    "|tkn_doc_content_column|Column contains document content|\n",
    "|tkn_text_lang|Specify language used in the text content for better text splitting if needed|\n",
    "|tkn_chunk_size|Specify >0 value to tokenize each row/doc in chunks of characters (rounded in words)|\n",
    "```"
   ]
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  {
   "cell_type": "markdown",
   "id": "ebf1f782-0e61-485c-8670-81066beb734c",
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    "##### ***** Import required classes and modules"
   ]
  },
  {
   "cell_type": "code",
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   "id": "9669273a-8fcc-4b40-9b20-8df658e2ab58",
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   "source": [
    "from dpk_tokenization.transform_python import Tokenization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7234563c-2924-4150-8a31-4aec98c1bf33",
   "metadata": {},
   "source": [
    "##### ***** Setup runtime parameters for this transform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "badafb96-64d2-4bb8-9f3e-b23713fd5c3f",
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   "source": [
    "Tokenization(input_folder= \"test-data/ds02/input\",\n",
    "        output_folder= \"output\",\n",
    "        tkn_tokenizer=  \"hf-internal-testing/llama-tokenizer\",\n",
    "        tkn_chunk_size= 20_000).transform()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3df5adf-4717-4a03-864d-9151cd3f134b",
   "metadata": {},
   "source": [
    "##### **** The specified folder will include the transformed parquet files."
   ]
  },
  {
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   "execution_count": null,
   "id": "7276fe84-6512-4605-ab65-747351e13a7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "glob.glob(\"output/*\")"
   ]
  },
  {
   "cell_type": "code",
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   "id": "845a75cf-f4a9-467d-87fa-ccbac1c9beb8",
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