update examples
Former-commit-id: d6bf6231290d79eb3a63e711f18fa711ef18a4f6
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@@ -11,6 +11,8 @@
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- [推理 LoRA 模型](#推理-lora-模型)
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- [杂项](#杂项)
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使用 `CUDA_VISIBLE_DEVICES`(GPU)或 `ASCEND_RT_VISIBLE_DEVICES`(NPU)选择计算设备。
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## 示例
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### LoRA 微调
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@@ -87,7 +89,7 @@ FORCE_TORCHRUN=1 NNODES=2 RANK=1 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llama
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#### 使用 DeepSpeed ZeRO-3 平均分配显存
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```bash
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FORCE_TORCHRUN=1 llamafactory-cli train examples/train_lora/llama3_lora_sft_ds.yaml
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FORCE_TORCHRUN=1 llamafactory-cli train examples/train_lora/llama3_lora_sft_ds3.yaml
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```
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### QLoRA 微调
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@@ -121,14 +123,14 @@ llamafactory-cli train examples/train_qlora/llama3_lora_sft_aqlm.yaml
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#### 在单机上进行指令监督微调
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```bash
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FORCE_TORCHRUN=1 llamafactory-cli train examples/train_full/llama3_full_sft.yaml
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FORCE_TORCHRUN=1 llamafactory-cli train examples/train_full/llama3_full_sft_ds3.yaml
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```
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#### 在多机上进行指令监督微调
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```bash
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FORCE_TORCHRUN=1 NNODES=2 RANK=0 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llamafactory-cli train examples/train_full/llama3_full_sft.yaml
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FORCE_TORCHRUN=1 NNODES=2 RANK=1 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llamafactory-cli train examples/train_full/llama3_full_sft.yaml
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FORCE_TORCHRUN=1 NNODES=2 RANK=0 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llamafactory-cli train examples/train_full/llama3_full_sft_ds3.yaml
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FORCE_TORCHRUN=1 NNODES=2 RANK=1 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llamafactory-cli train examples/train_full/llama3_full_sft_ds3.yaml
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```
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#### 批量预测并计算 BLEU 和 ROUGE 分数
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