diff --git a/llm/mthreads/llama/README.md b/llm/mthreads/llama/README.md
new file mode 100644
index 000000000000..c28694aa9268
--- /dev/null
+++ b/llm/mthreads/llama/README.md
@@ -0,0 +1,78 @@
+## 🚣‍♂️ 使用 PaddleNLP 在 MTT S4000 下跑通 llama2-13b 模型预训练 🚣
+PaddleNLP在MTT®S4000([了解摩尔线程](https://www.mthreads.com/))上对 llama2-13B 模型进行了深度适配和优化，下面给出详细安装步骤。
+
+##  🚀 快速开始 🚀
+
+### （0）在开始之前，您需要有一台 MTT S4000 机器，对此机器的系统要求如下：
+
+ | 芯片类型 | 卡型号 | 驱动版本 |
+ | --- | --- | --- |
+ | MTT | S4000 | 2.7.0 |
+
+
+### （1）环境准备：(这将花费您5～15min 时间)
+1. 拉取镜像
+```
+# 注意此镜像仅为开发环境，镜像中不包含预编译的飞桨安装包
+docker pull core.harbor.ghidc.mthreads.com:30003/library/musa-paddle-dev:dev3.1.0-paddle-2.6-v13
+```
+2. 参考如下命令启动容器
+```
+docker run it  --env MTHREADS_VISIBLE_DEVICES=all --ipc=host --net=host --cap-add=SYS_PTRACE --shm-size=40g core.harbor.ghidc.mthreads.com:30003/library/musa-paddle-dev:dev3.1.0-paddle-2.6-v13
+```
+3. 安装 paddle
+```
+# paddlepaddle『飞桨』深度学习框架，提供运算基础能力
+git clone git@github.com:PaddlePaddle/Paddle.git -b release-musa/2.6
+git submodule update --init --recursive
+bash build.sh
+```
+4. 克隆 PaddleNLP 仓库代码，并安装依赖
+```
+# PaddleNLP是基于paddlepaddle『飞桨』的自然语言处理和大语言模型(LLM)开发库，存放了基于『飞桨』框架实现的各种大模型，llama2-13B模型也包含其中。为了便于您更好地使用PaddleNLP，您需要clone整个仓库。
+git clone git@github.com:shang-mt/PaddleNLP.git -b mthreads-llama-13B
+cd PaddleNLP
+python -m pip install -r requirements.txt
+python -m pip install -e .
+```
+
+### （2）训练：
+1. 多机多卡训练
+
+执行如下命令进行训练：
+```bash
+cd llm/
+bash run_dist.sh 10.10.10.123 # 假设master ip 为10.10.10.123，在不同节点上执行此命令
+```
+成功运行后，可以查看到训练日志的生成，样例如下：
+```bash
+/home/baidu_test/miniconda3/envs/sci-baidu/lib/python3.10/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils.
+  warnings.warn("Setuptools is replacing distutils.")
+[2024-04-30 17:28:18,614] [ WARNING] - evaluation_strategy reset to IntervalStrategy.STEPS for do_eval is True. you can also set evaluation_strategy='epoch'.
+[2024-04-30 17:28:18,614] [    INFO] distributed_strategy.py:214 - distributed strategy initialized
+[2024-04-30 17:28:18,614] [    INFO] - PP configs:{'micro_batch_size': 2, 'accumulate_steps': 256, 'schedule_mode': '1F1B', 'p2p_cache_shape': True, 'enable_partial_send_recv': False}, use master_grad: 1
+[2024-04-30 17:28:18,614] [ WARNING] - In pipeline model, the evaluation also shares same setting with training. We will enforce that per_device_eval_batch_size=per_device_train_batch_size * gradient_accumulation_steps.
+[2024-04-30 17:28:18,615] [    INFO] - using pipeline configs:{'delay_scale_loss': False, 'dp_comm_overlap': False, 'sharding_comm_overlap': False, 'enable_timer': False, 'release_gradients': False}
+/home/baidu_test/zhonghui03/PaddleNLP/paddlenlp/trainer/training_args.py:1107: UserWarning: For pipeline parallel with sharding, the sharding overlap and tensor fusion should be configured in pipeline_parallel_config."enable_stage1_tensor_fusion" and "enable_stage1_overlap" in sharding_parallel_config will be ignored.
+  warnings.warn(
+======================= Modified FLAGS detected =======================
+FLAGS(name='FLAGS_selected_gpus', current_value='0', default_value='')
+=======================================================================
+I0430 17:28:18.616860 1117373 tcp_utils.cc:181] The server starts to listen on IP_ANY:44264
+I0430 17:28:18.617025 1117373 tcp_utils.cc:130] Successfully connected to 10.3.5.1:44264
+I0430 17:28:21.722956 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+I0430 17:28:21.724152 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+[2024-04-30 17:28:21,724] [    INFO] topology.py:358 - Total 8 pipe comm group(s) create successfully!
+W0430 17:28:21.727821 1117373 gpu_resources.cc:119] Please NOTE: device: 0, GPU Compute Capability: 8.0, Driver API Version: 12.0, Runtime API Version: 11.7
+W0430 17:28:21.730523 1117373 gpu_resources.cc:164] device: 0, cuDNN Version: 8.9.
+[2024-04-30 17:28:28,398] [    INFO] topology.py:358 - Total 32 data comm group(s) create successfully!
+I0430 17:28:28.399701 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+[2024-04-30 17:28:28,400] [    INFO] topology.py:358 - Total 16 model comm group(s) create successfully!
+I0430 17:28:28.400249 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+[2024-04-30 17:28:28,400] [    INFO] topology.py:358 - Total 8 sharding comm group(s) create successfully!
+I0430 17:28:28.400563 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+I0430 17:28:28.400646 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+I0430 17:28:28.400784 1117373 process_group_nccl.cc:129] ProcessGroupNCCL pg_timeout_ 1800000
+[2024-04-30 17:28:28,401] [    INFO] topology.py:288 - HybridParallelInfo: rank_id: 0, mp_degree: 2, sharding_degree: 4, pp_degree: 4, dp_degree: 1, sep_degree: 1, mp_group: [0, 1],  sharding_group: [0, 2, 4, 6], pp_group: [0, 8, 16, 24], dp_group: [0], sep:group: None, check/clip group: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]
+[2024-04-30 17:28:28,402] [    INFO] -     +==============================================================================+
+```