C++ β Python Transformer (16.4M params)
Encoder-decoder transformer trained from scratch for C++ β Python code translation. Trained on XLCoST on a single GTX 1650 4 GB GPU. Best checkpoint at epoch 19, val_loss 2.0474.
Architecture
- 4 encoder + 4 decoder layers, pre-norm
- d_model 256, 8 heads, d_ff 512
- Sinusoidal positional encoding
- Greedy decoding at inference
- 16.4M parameters
Files
best_model.ptβ full PyTorch checkpoint (model state, optimizer state, src/tgt vocabularies). 189 MB.
Load
from model import build_transformer
import torch
ckpt = torch.load('best_model.pt', map_location='cpu')
model = build_transformer(
src_vocab_size=len(ckpt['src_vocab']),
tgt_vocab_size=len(ckpt['tgt_vocab']),
src_seq_len=300, tgt_seq_len=300,
d_model=256, N=4, h=8, dropout=0.0, d_ff=512,
)
model.load_state_dict(ckpt['model_state'])
model.eval()
Full training and inference code: github.com/debtirthasaha/cpp-to-python-transformer
Writeup
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