class_docstr: Transformer pure decoder stack for language modelling.
  
  Args:
    config: TransformerConfig dataclass containing hyperparameters.
code: def __init__(self, config: TransformerConfig, *, rngs: nnx.Rngs):
      self.config = config
      self.decoder = Decoder(
          config=config, shared_embedding=None, rngs=rngs
      )
  
imports: from __future__ import annotations
  import dataclasses
  from typing import Any, Optional
  import jax
  import jax.numpy
  import numpy
  from jax import lax
  from flax.experimental import nnx
  from flax.experimental.nnx.nnx import flaglib
  from flax.experimental.nnx.examples.lm1b.configs import default
label_desc: Use image node_id 1 to create a new TransformerLM object from inherited base classes: nnx with example: obj = TransformerLM(config)