初始化项目，由ModelHub XC社区提供模型

Model: Tencent-Hunyuan/Hy-MT2-7B-GGUF
Source: Original Platform

train/llama_factory_support/train_lf.sh

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+#!/bin/bash
+# ============================================================================
+# LLaMA Factory training launch script for HYV3
+#
+# This script sets up the environment and launches training via torchrun.
+#
+# We use train_hy_v3.py as the entry point (not llamafactory-cli)
+# because we need to inject HYV3-specific monkey-patches and register
+# the hy_v3 chat template BEFORE LLaMA Factory starts.
+# train_hy_v3.py directly calls run_exp() in each torchrun worker,
+# ensuring all patches are active.
+#
+# Usage:
+#   Single node:  bash train_lf.sh
+#   Multi-node:   Run this script on EACH node with the same IP_LIST.
+#                 IP_LIST="10.0.0.1,10.0.0.2" bash train_lf.sh
+# ============================================================================
+
+set -euo pipefail
+
+# -------------------- Network Configuration --------------------
+NET_TYPE="high"
+export NCCL_DEBUG=WARN
+export NCCL_P2P_LEVEL=NVL
+export NCCL_IB_TIMEOUT=24
+export NCCL_NVLS_ENABLE=0
+export NCCL_MPI_PROFILE_PRIMS_ENABLE=0
+export CUDA_DEVICE_MAX_CONNECTIONS=1
+export TORCH_NCCL_HEARTBEAT_TIMEOUT_SEC=3600
+if [[ "${NET_TYPE}" = "low" ]]; then
+    export NCCL_SOCKET_IFNAME=eth1
+    export NCCL_IB_GID_INDEX=3
+    export NCCL_IB_HCA=mlx5_2:1
+    export NCCL_IB_SL=3
+    export NCCL_CHECK_DISABLE=1
+    export NCCL_P2P_DISABLE=0
+    export NCCL_LL_THRESHOLD=16384
+    export NCCL_IB_CUDA_SUPPORT=1
+else
+    export NCCL_IB_GID_INDEX=3
+    export NCCL_IB_SL=3
+    export NCCL_CHECK_DISABLE=1
+    export NCCL_P2P_DISABLE=0
+    export NCCL_IB_DISABLE=0
+    export NCCL_LL_THRESHOLD=16384
+    export NCCL_IB_CUDA_SUPPORT=1
+    export NCCL_SOCKET_IFNAME=bond1
+    export UCX_NET_DEVICES=bond1
+    export NCCL_IB_HCA=mlx5_bond_1,mlx5_bond_5,mlx5_bond_3,mlx5_bond_7,mlx5_bond_4,mlx5_bond_8,mlx5_bond_2,mlx5_bond_6
+    export NCCL_COLLNET_ENABLE=0
+    export SHARP_COLL_ENABLE_SAT=0
+    export NCCL_NET_GDR_LEVEL=2
+    export NCCL_IB_QPS_PER_CONNECTION=4
+    export NCCL_IB_TC=160
+    export NCCL_PXN_DISABLE=1
+fi
+
+# Skip LLaMA Factory version check (we use a newer transformers branch)
+export DISABLE_VERSION_CHECK=1
+
+# -------------------- Node Configuration --------------------
+export HOST_GPU_NUM=8
+# IP list, comma separated. e.g. "10.0.0.1,10.0.0.2" or single node "127.0.0.1"
+export IP_LIST=${IP_LIST:-"127.0.0.1"}
+
+MASTER_PORT=${MASTER_PORT:-29500}
+
+IFS=',' read -ra IP_ARRAY <<< "$IP_LIST"
+NODES=${#IP_ARRAY[@]}
+MASTER_ADDR=${IP_ARRAY[0]}
+
+# -------------------- Paths --------------------
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+YAML_FILE="${YAML_FILE:-${SCRIPT_DIR}/hy_v3_full_sft.yaml}"
+ENTRY_SCRIPT="${SCRIPT_DIR}/train_hy_v3.py"
+
+# -------------------- Distributed Environment --------------------
+export MASTER_ADDR="${MASTER_ADDR}"
+export MASTER_PORT="${MASTER_PORT}"
+export NNODES="${NODES}"
+
+if [ ${NODES} -gt 1 ]; then
+    # Determine local node rank by matching local IP against IP_LIST
+    LOCAL_IP=$(hostname -i | awk '{print $1}')
+    NODE_RANK=0
+    for i in "${!IP_ARRAY[@]}"; do
+        if [[ "${IP_ARRAY[$i]}" == "${LOCAL_IP}" ]]; then
+            NODE_RANK=$i
+            break
+        fi
+    done
+    export RANK="${NODE_RANK}"
+else
+    export RANK=0
+fi
+
+echo "============================================"
+echo "  HYV3 LLaMA Factory Training"
+echo "  Nodes: ${NNODES}, Rank: ${RANK}"
+echo "  Master: ${MASTER_ADDR}:${MASTER_PORT}"
+echo "  GPUs per node: ${HOST_GPU_NUM}"
+echo "  Total GPUs: $((NODES * HOST_GPU_NUM))"
+echo "============================================"
+
+# -------------------- Launch --------------------
+# We launch torchrun directly (instead of FORCE_TORCHRUN) so that each
+# worker process runs train_hy_v3.py with all HYV3 patches applied.
+torchrun \
+    --nnodes "${NNODES}" \
+    --node_rank "${RANK}" \
+    --nproc_per_node "${HOST_GPU_NUM}" \
+    --master_addr "${MASTER_ADDR}" \
+    --master_port "${MASTER_PORT}" \
+    "${ENTRY_SCRIPT}" "${YAML_FILE}"