| from src.model import GTransformerConfig, GTransformerForCausalLM |
| from safetensors.torch import save_file |
| import torch |
|
|
| |
| config = GTransformerConfig( |
| vocab_size=65536, |
| hidden_size=1024, |
| intermediate_size=4096, |
| num_hidden_layers=12, |
| num_attention_heads=16, |
| use_low_rank_ffn=True, |
| use_entropy_gate=True, |
| use_flash_attention=True, |
| informational_constant_kI=2.612e-20, |
| ) |
|
|
| |
| model = GTransformerForCausalLM(config) |
|
|
| |
| for name, param in model.named_parameters(): |
| if param.dim() > 1: |
| torch.nn.init.xavier_normal_(param) |
| else: |
| torch.nn.init.zeros_(param) |
|
|
| |
| state_dict = model.state_dict() |
| save_file(state_dict, "pytorch_model.safetensors") |
|
|
| print("✅ File bobot berhasil dibuat: pytorch_model.safetensors") |
| print(f"Total parameter: {sum(p.numel() for p in model.parameters())/1e6:.2f} juta") |
|
|