code: def model_from_config(config: ml_collections.ConfigDict):
      """Builds a text classification model from a config."""
      model = models.TextClassifier(
          embedding_size=config.embedding_size,
          hidden_size=config.hidden_size,
          vocab_size=config.vocab_size,
          output_size=config.output_size,
          dropout_rate=config.dropout_rate,
          word_dropout_rate=config.word_dropout_rate,
          unk_idx=config.unk_idx,
      )
      return model
  
imports: from typing import Any, Callable, Dict, Iterable, Optional, Sequence, Tuple, Union
  from absl import logging
  from flax import struct
  from flax.metrics import tensorboard
  from flax.training import train_state
  import jax
  import jax.numpy
  import ml_collections
  import numpy
  import optax
  import tensorflow
  import input_pipeline
  import models
label_desc: Use image node_id 5 for calling a global function with example usage: model_from_config(config) and returns: model