# modeling_micro_distill.py
# Custom model architecture for micro-distill-grpo-vae

import torch
import torch.nn as nn
from transformers import GPT2PreTrainedModel, GPT2Config

class MicroDistillForCausalLM(GPT2PreTrainedModel):
    def __init__(self, config):
        super().__init__(config)
        self.config = config
        
    # ... modeling code ...
    
    def forward(self, input_ids=None, attention_mask=None, **kwargs):
        # Forward pass implementation
        pass