update modelzoo std

README.md

 # LLama_FT
 
-## 模型介绍
-LLama是一个基础语言模型的集合,参数范围从7B到65B。在数万亿的tokens上训练出的模型，并表明可以专门使用公开可用的数据集来训练最先进的模型，而不依赖于专有的和不可访问的数据集。
+## 论文
+- [https://arxiv.org/pdf/2302.13971.pdf](https://arxiv.org/pdf/2302.13971.pdf)
 
 ## 模型结构
-
 LLAMA网络基于 Transformer 架构。提出了各种改进，并用于不同的模型，例如 PaLM。以下是与原始架构的主要区别：
 预归一化。为了提高训练稳定性，对每个transformer 子层的输入进行归一化，而不是对输出进行归一化。使用 RMSNorm 归一化函数。
 SwiGLU 激活函数 [PaLM]。使用 SwiGLU 激活函数替换 ReLU 非线性以提高性能。使用 2 /3 4d 的维度而不是 PaLM 中的 4d。
 旋转嵌入。移除了绝对位置嵌入，而是添加了旋转位置嵌入 (RoPE)，在网络的每一层。
 
-## 推理
+## 模型介绍
+LLama是一个基础语言模型的集合,参数范围从7B到65B。在数万亿的tokens上训练出的模型，并表明可以专门使用公开可用的数据集来训练最先进的模型，而不依赖于专有的和不可访问的数据集。
 
-### 环境配置
+## 环境配置
 
 提供[光源](https://www.sourcefind.cn/#/service-details)拉取推理的docker镜像：
-* 推理镜像：docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:fastertransformer-dtk23.04-latest
+```
+docker pull docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:fastertransformer-dtk23.04-latest
+docker run -it --name llama --shm-size=32G  --device=/dev/kfd --device=/dev/dri/ --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --ulimit memlock=-1:-1 --ipc=host --network host --group-add video docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:fastertransformer-dtk23.04-latest /bin/bash
+```
+
+镜像版本依赖：
+* DTK驱动：dtk23.04
+* Pytorch: 1.10
+* python: python3.8
 
 激活镜像环境：
 `source /opt/dtk-23.04/env.sh`
 
+## 数据集
+训练数据集：CCNet [67%], C4 [15%], GitHub [4.5%], Wikipedia [4.5%], Books [4.5%], ArXiv [2.5%], Stack Exchange[2%]，Wikipedia和Books包括以下语言的数据：bg, ca, cs, da, de, en, es, fr, hr, hu, it, nl, pl, pt, ro, ru, sl, sr, sv, uk。评估数据集：BoolQ, PIQA, SIQA, HellaSwag, WinoGrande, ARC, OpenBookQA, NaturalQuestions, TriviaQA, RACE, MMLU, BIG-bench hard, GSM8k, RealToxicityPrompts, WinoGender, CrowS-Pairs。
 
+## 推理
 ### 编译
 
 ```
@@ -32,10 +43,12 @@ make -j12
 
 ### 模型下载
 
+```
 [llama 7B](https://huggingface.co/decapoda-research/llama-7b-hf)
 [llama 13b](https://huggingface.co/decapoda-research/llama-13b-hf)
 [llama 30B](https://huggingface.co/decapoda-research/llama-30b-hf)
 [llama 65b](https://huggingface.co/decapoda-research/llama-65b-hf)
+```
 
 模型转换
 
@@ -112,6 +125,30 @@ layernorm_eps=rms_norm_eps
 vocab_size=vocab_size
 ```
 
+## result
+build/
+    out
+
+## 精度
+测试数据："I believe the meaning of life is" (token id: 306, 4658, 278, 6593, 310, 2834, 338)，使用的加速卡:1张 DCU-Z100L-32G
+准确性数据：
+| 数据类型 | batch size | temperate | input len | output len |
+| :------: | :------: | :------: | :------: |:------: |
+| fp16 | 1 | 0 | 7 | 256 |
+
+输出：
+```
+I believe the meaning of life is to live it to the fullest. I believe that we are all here for a reason and that we are all here to help each other. I believe that we are all here to learn and grow and that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here to help each other learn and grow. I believe that we are all here
+```
+
+## 应用场景
+
+### 算法类别
+NLP
+
+### 热点应用行业
+金融,科研,教育
+
 ## 源码仓库及问题反馈
 * https://developer.hpccube.com/codes/modelzoo/llama_ft
 

model.properties

+# 模型唯一标识
+modelCode = 358
 # 模型名称
-modelName=LLama_FT
+modelName=llama_fastertransformer
 # 模型描述
 modelDescription=LLama是一个基础语言模型的集合,参数范围从7B到65B。在数万亿的tokens上训练出的模型,并表明可以专门使用公开可用的数据集来训练最先进的模型。
 # 应用场景