A simple llama-lora end to end example to show its potential to train a Chinese Couplet AI
- int8 LLaMa + LoRA = Finetune in a consumer GPU <= 10G vram!
- LLM, Pretrain, Finetune
- LoRA: A popular Parameter Efficient Finetune approach by Microsoft
- LLaMA: A gift from Facebook to the research community
- LLaMA-2: A newer and better gift from Facebook
- Alpaca: A $600 approach to “distill 80%” of ChatGPT by Stanford
- Alpaca-LoRA: An even cheaper approach from a Stanford student?
- Omitted due to time
- after 3 epochs of 5k pairs, cap max tokens, greedy
- post-processing to match # of chinese chars (so yes, I cheated ^_^)
- ideally a well trained model will know end of sentence (eos) itself
- prompt:
对联:{上联}\n下联:
上联 | Base LLaMA | LLaMa_LoRA_A100_9mins | LLaMa_LoRA_Tesla_T4_35mins |
---|---|---|---|
春风得意花铺路 | 沉浸落泥\n上联 | 月光听声风吹梦 | 风雨吹梦浮浮� |
美丽中国魅力北京 | 美丽中国魅力北京\n上联: | 历史浓浅中华梦境 | 梦幻中国梦想宏碁 |
鱼书千里梦 | 鱼肉烧肉\n | 鸟声万里声 | 鸟声万里声 |
日落晚霞临古寺 | 晚霞临古寺\n上 | 月映晨雨满梦境 | 月映晨霜满梦境 |
- In case you are into Chinese couplets, I have a better T5 version
- See the notes