code: def encoder_config() -> LLMEncoderConfig:
      """Create a baseline LLMEncoderConfig.
  
      Returns:
          A baseline LLMEncoderConfig with a small model, no adapter, and no quantization
      """
      return LLMEncoderConfig(
          type="llm",
          max_sequence_length=256,
          base_model="HuggingFaceH4/tiny-random-LlamaForCausalLM",
          adapter=None,
          quantization=None,
      )
  
imports: import copy
  import pytest
  import torch
  import torch.nn
  from transformers import AutoConfig, PreTrainedModel
  from ludwig.encoders.text_encoders import LLMEncoder
  from ludwig.schema.encoders.text_encoders import LLMEncoderConfig
  from ludwig.schema.llms.peft import BaseAdapterConfig, LoraConfig
  from ludwig.utils.llm_utils import get_context_len
label_desc: Use image node_id 1 for calling a global function with example usage: encoder_config() and returns: LLMEncoderConfig