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# 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 |