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https://github.com/hiyouga/LLaMA-Factory.git
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update examples
Former-commit-id: b87f8f15194923392d1a1c3d3c617b463cdd8379
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@ -15,8 +15,8 @@ fsdp_config:
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machine_rank: 0
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main_training_function: main
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mixed_precision: fp16
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num_machines: 1
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num_processes: 2
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num_machines: 1 # the number of nodes
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num_processes: 2 # the number of GPUs in all nodes
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rdzv_backend: static
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same_network: true
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tpu_env: []
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@ -8,8 +8,8 @@ main_process_ip: 192.168.0.1
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main_process_port: 29555
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main_training_function: main
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mixed_precision: fp16
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num_machines: 2
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num_processes: 16
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num_machines: 2 # the number of nodes
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num_processes: 16 # the number of GPUs in all nodes
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rdzv_backend: static
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same_network: true
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tpu_env: []
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@ -6,8 +6,8 @@ gpu_ids: all
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machine_rank: 0
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main_training_function: main
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mixed_precision: fp16
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num_machines: 1
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num_processes: 4
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num_machines: 1 # the number of nodes
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num_processes: 4 # the number of GPUs in all nodes
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rdzv_backend: static
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same_network: true
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tpu_env: []
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@ -8,8 +8,8 @@ main_process_ip: 192.168.0.1
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main_process_port: 29555
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main_training_function: main
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mixed_precision: fp16
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num_machines: 2
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num_processes: 16
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num_machines: 2 # the number of nodes
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num_processes: 16 # the number of GPUs in all nodes
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rdzv_backend: static
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same_network: true
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tpu_env: []
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@ -1,4 +1,5 @@
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#!/bin/bash
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# DO NOT use quantized model or quantization_bit when merging lora weights
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CUDA_VISIBLE_DEVICES= python ../../src/export_model.py \
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--model_name_or_path meta-llama/Llama-2-7b-hf \
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