support batch infer in vllm
Former-commit-id: 3ef5ed3b9a44eed2f7e3ff221dfc343d0a97c0b5
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@@ -13,6 +13,8 @@ Make sure to execute these commands in the `LLaMA-Factory` directory.
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Use `CUDA_VISIBLE_DEVICES` (GPU) or `ASCEND_RT_VISIBLE_DEVICES` (NPU) to choose computing devices.
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By default, LLaMA-Factory uses all visible computing devices.
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## Examples
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### LoRA Fine-Tuning
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@@ -80,12 +82,6 @@ llamafactory-cli train examples/train_lora/llama3_preprocess.yaml
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llamafactory-cli eval examples/train_lora/llama3_lora_eval.yaml
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```
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#### Batch Predicting and Computing BLEU and ROUGE Scores
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```bash
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llamafactory-cli train examples/train_lora/llama3_lora_predict.yaml
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```
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#### Supervised Fine-Tuning on Multiple Nodes
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```bash
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@@ -146,12 +142,6 @@ FORCE_TORCHRUN=1 NNODES=2 RANK=1 MASTER_ADDR=192.168.0.1 MASTER_PORT=29500 llama
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FORCE_TORCHRUN=1 llamafactory-cli train examples/train_full/qwen2vl_full_sft.yaml
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```
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#### Batch Predicting and Computing BLEU and ROUGE Scores
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```bash
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llamafactory-cli train examples/train_full/llama3_full_predict.yaml
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```
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### Merging LoRA Adapters and Quantization
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#### Merge LoRA Adapters
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@@ -170,13 +160,19 @@ llamafactory-cli export examples/merge_lora/llama3_gptq.yaml
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### Inferring LoRA Fine-Tuned Models
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#### Use CLI
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#### Batch Generation using vLLM Tensor Parallel
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```
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python scripts/vllm_infer.py --model_name_or_path path_to_merged_model --dataset alpaca_en_demo
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```
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#### Use CLI ChatBox
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```bash
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llamafactory-cli chat examples/inference/llama3_lora_sft.yaml
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```
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#### Use Web UI
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#### Use Web UI ChatBox
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```bash
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llamafactory-cli webchat examples/inference/llama3_lora_sft.yaml
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@@ -238,3 +234,9 @@ llamafactory-cli train examples/extras/llama_pro/llama3_freeze_sft.yaml
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```bash
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bash examples/extras/fsdp_qlora/train.sh
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```
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#### Computing BLEU and ROUGE Scores
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```bash
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llamafactory-cli train examples/extras/nlg_eval/llama3_lora_predict.yaml
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```
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