gpt/models/gpt4_model.py

"""
Gpt4 model implementation
Parameters: {
  "n_head": 200, 
  "active_experts": 8, 
  "n_embd": 18432, 
  "params": "1.7T", 
  "n_layer": 200, 
  "experts": 200, 
  "block_size": 128000, 
  "moe": true
}
"""

import torch
import torch.nn as nn
from configs.gpt4_config import Gpt4Config

# Mixture of Experts implementation
class Gpt4MoETransformer(nn.Module):
    def __init__(self, config):
        super().__init__()
        self.config = config
        # MoE architecture
        self.num_experts = config.num_experts
        self.num_active_experts = config.num_active_experts
        print("Initializing {} MoE model with {} parameters".format(
            "Gpt4", config.parameter_count))
        print("Using {} experts with {} active per token".format(
            self.num_experts, self.num_active_experts))
        
    def forward(self, x, **kwargs):
        # This implementation would handle the MoE routing and forward pass
        pass