初始化项目，由ModelHub XC社区提供模型

Model: ayh015/myLightningOPD
Source: Original Platform

configs/sft/run_sft.sh

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+#!/usr/bin/env bash
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+# Step 2: Run SFT training with LlamaFactory.
+#
+# Required environment variables:
+#   CONFIG_YAML - Name of the SFT config file in configs/sft/ (e.g. qwen3-4b-base-sft-qwen3-8b.yaml)
+#   OUTPUT_DIR  - Directory for the SFT checkpoint output
+#
+# Optional:
+#   NUM_NODES   - Number of nodes (default: 4)
+#   NUM_GPUS    - GPUs per node (default: 8)
+#   MASTER_ADDR - Master node address (default: localhost)
+#
+# Prerequisites:
+#   - LlamaFactory installed (pip install llamafactory)
+#   - SFT data generated by Step 1 and registered in LlamaFactory's dataset_info.json
+
+set -euo pipefail
+
+: "${CONFIG_YAML:?Set CONFIG_YAML (e.g. qwen3-4b-base-sft-qwen3-8b.yaml)}"
+: "${OUTPUT_DIR:?Set OUTPUT_DIR for SFT checkpoint output}"
+
+NUM_NODES="${NUM_NODES:-4}"
+NUM_GPUS="${NUM_GPUS:-8}"
+MASTER_ADDR="${MASTER_ADDR:-localhost}"
+MASTER_PORT="${MASTER_PORT:-29500}"
+
+# torchrun \
+#     --nnodes "${NUM_NODES}" \
+#     --nproc_per_node="${NUM_GPUS}" \
+#     --rdzv_id $RANDOM \
+#     --rdzv_backend c10d \
+#     --rdzv_endpoint "${MASTER_ADDR}:29500" \
+#     -m llamafactory.cli.train \
+#     "configs/sft/${CONFIG_YAML}" \
+#     "dataset_dir=configs/sft" \
+#     "output_dir=${OUTPUT_DIR}"
+
+FORCE_TORCHRUN=1 \
+NNODES="${NUM_NODES}" \
+NPROC_PER_NODE="${NUM_GPUS}" \
+MASTER_ADDR="${MASTER_ADDR}" \
+MASTER_PORT="${MASTER_PORT}" \
+llamafactory-cli train \
+    "configs/sft/${CONFIG_YAML}" \
+    "dataset_dir=configs/sft" \
+    "output_dir=${OUTPUT_DIR}"