modeling_custom.py

from transformers.models.llama.modeling_llama import LlamaForCausalLM, LlamaConfig
import torch
from transformers.utils import logging

logger = logging.get_logger(__name__)

class CustomLlamaForCausalLM(LlamaForCausalLM):
    def __init__(self, config: LlamaConfig):
        super().__init__(config)
        logger.info("CustomLlamaForCausalLM initialized with conceptual features documented in config.")
        if getattr(config, 'conceptual_features', {}).get('grouping_logic'):
             logger.info(f"Conceptual grouping logic enabled with size {config.conceptual_features.get('group_size', 'N/A')}")
        if getattr(config, 'conceptual_features', {}).get('long_context_optimization'):
             logger.info("Conceptual long context optimization hint detected.")