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README.md

GPT-Pretrain

Usage

Make it simple

python lit_train.py --model_name gpt2 --use_tril_attention_mask
python lit_export.py --version 0
python generate.py --model_name_or_path exports/version_0 --tokenizer_name_or_path gpt2

📝 Note: Training with a "--use_tril_attention_mask" is recommended. However, huggingface model implementions might not support 2D attention mask. You may write a custom model to support 2D attention mask, just like what I did in custom_models/gpt2.

Train on multiple GPUs

python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy fsdp # default and recommended
python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy deepspeed
python lit_train.py --model_name gpt2 --use_tril_attention_mask --strategy ddp

Reduce CUDA memory cost

  • half precision
    python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16
    
    python lit_train.py --model_name gpt2 --use_tril_attention_mask --fp16
    
  • smaller batch size & accumulate grad batches
    python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \
        --train_batch_size 2 --val_batch_size 4 --accumulate_grad_batches 128
    
  • cpu_offload
    python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \
        --strategy fsdp_cpu_offload
    
    python lit_train.py --model_name gpt2 --use_tril_attention_mask --bf16 \
        --strategy deepspeed_stage_3_offload