Tungsong
Tungsong
**I trained Alpaca-LoRA model with params:** base_model: /usr/local/dbbd/model/llama-7b-hf data_path: alpaca_data.json output_dir: ./lora-alpaca batch_size: 128 micro_batch_size: 4 num_epochs: 2 learning_rate: 0.0001 cutoff_len: 512 val_set_size: 2000 lora_r: 8 lora_alpha: 16 lora_dropout: 0.05...
I have two T4 on my machine, and I want to improve training efficiency, because it has enough memory when I use the default params  I tried to update...
微调完给出的answer一直在重复同一句话,而且也不是答案 微调方式参考的https://github.com/27182812/ChatGLM-LLaMA-chinese-insturct 训练了3个epoch,效果如下,请教有谁知道为什么会这样吗 
N次循环会初始化N次还是只初始化一次,怎么初始化的呢,不太懂这个α怎么来的,有什么作用 
多卡推理参考的ChatGLM-6B官方的多卡部署 https://github.com/THUDM/ChatGLM-6B#%E5%A4%9A%E5%8D%A1%E9%83%A8%E7%BD%B2
不懂这行代码有什么作用,引入时报错 