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LLaMA-Factory-Mirror
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update readme

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hiyouga 2024-03-28 18:35:11 +08:00
parent b19c14870d
commit 6c94305e47
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README.md
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@ -451,7 +451,7 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
```
> [!TIP]
> Use `--adapter_name_or_path path_to_sft_checkpoint,path_to_ppo_checkpoint` to infer the fine-tuned model.
> Use `--adapter_name_or_path path_to_sft_checkpoint,path_to_ppo_checkpoint` to infer the fine-tuned model if `--create_new_adapter` was enabled.
> [!WARNING]
> Use `--per_device_train_batch_size=1` for LLaMA-2 models in fp16 PPO training.
@ -482,7 +482,7 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
```
> [!TIP]
> Use `--adapter_name_or_path path_to_sft_checkpoint,path_to_dpo_checkpoint` to infer the fine-tuned model.
> Use `--adapter_name_or_path path_to_sft_checkpoint,path_to_dpo_checkpoint` to infer the fine-tuned model if `--create_new_adapter` was enabled.
### Distributed Training
@ -570,7 +570,7 @@ deepspeed --num_gpus 8 src/train_bash.py \
### Merge LoRA weights and export model
```bash
CUDA_VISIBLE_DEVICES=0 python src/export_model.py \
CUDA_VISIBLE_DEVICES= python src/export_model.py \
--model_name_or_path path_to_llama_model \
--adapter_name_or_path path_to_checkpoint \
--template default \

6
README_zh.md
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@ -450,7 +450,7 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
```
> [!TIP]
> 使用 `--adapter_name_or_path path_to_sft_checkpoint,path_to_ppo_checkpoint` 来进行微调模型的推理。
> 如果开启了 `--create_new_adapter`，则使用 `--adapter_name_or_path path_to_sft_checkpoint,path_to_ppo_checkpoint` 来进行微调模型的推理。
> [!WARNING]
> 如果使用 fp16 精度进行 LLaMA-2 模型的 PPO 训练，请使用 `--per_device_train_batch_size=1`。
@ -481,7 +481,7 @@ CUDA_VISIBLE_DEVICES=0 python src/train_bash.py \
```
> [!TIP]
> 使用 `--adapter_name_or_path path_to_sft_checkpoint,path_to_dpo_checkpoint` 来进行微调模型的推理。
> 如果开启了 `--create_new_adapter`，则使用 `--adapter_name_or_path path_to_sft_checkpoint,path_to_dpo_checkpoint` 来进行微调模型的推理。
### 多 GPU 分布式训练
@ -569,7 +569,7 @@ deepspeed --num_gpus 8 src/train_bash.py \
### 合并 LoRA 权重并导出模型
```bash
CUDA_VISIBLE_DEVICES=0 python src/export_model.py \
CUDA_VISIBLE_DEVICES= python src/export_model.py \
--model_name_or_path path_to_llama_model \
--adapter_name_or_path path_to_checkpoint \
--template default \