First add

Contributors.md

+# Contributors
+This file contains the list of everyone who contributed to the repository
+
+<br>
+<table>
+<th>Contributors1</th><th>Contributors2</th>  <tr>
+    <td><img src="xxx1">
+    <br>
+    <a href="xxx1">xxx1</a></td>
+    <td><img src="xxx2">
+    <br>
+    <a href="xxx2">xxx2</a></td>
+  </tr>
+</table>
+<br>
+
+### Thanks to everyone who helped in building this Repository :)

LICENSE

+Microsoft.
+Copyright (c) Microsoft Corporation.
+
+MIT License
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
\ No newline at end of file

README.md

+# Phi-3
+## 论文
+`Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone`
+- https://arxiv.org/abs/2404.14219
+
+## 模型结构
+基于transformer结构
+<div align=center>
+    <img src="./doc/transformers.jpg" witdh=300 height=400/>
+</div>
+
+## 算法原理
+Phi-3 模型是目前功能最强大、性价比最高的小型语言模型 (SLM)，在各种语言、推理、编码和数学基准测试中，其表现优于同等规模和下一个规模的模型。此版本扩大了客户的高质量模型选择范围，为他们编写和构建生成式 AI 应用程序提供了更多实用选择。
+
+## 环境配置
+-v 路径、docker_name和imageID根据实际情况修改
+
+### Docker（方法一）
+```
+docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
+
+docker run -it --network=host --privileged=true --name=docker_name --device=/dev/kfd --device=/dev/dri --ipc=host --shm-size=32G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro imageID /bin/bash
+
+cd /your_code_path/phi-3_pytorch
+pip install -r requirements.txt
+```
+
+### Dockerfile（方法二）
+```
+cd ./docker
+docker build --no-cache -t phi-3:latest .
+
+docker run -it --network=host --privileged=true --name=docker_name --device=/dev/kfd --device=/dev/dri --ipc=host --shm-size=32G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined -u root -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro imageID /bin/bash
+
+cd /your_code_path/phi-3_pytorch
+pip install -r requirements.txt
+```
+
+### Anaconda（方法三）
+关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.hpccube.com/tool/)开发者社区下载安装。
+```
+DTK驱动：dtk24.04.1
+python：3.10
+torch：2.1
+vllm: 0.3.3
+```
+
+`Tips：以上dtk驱动、python等DCU相关工具版本需要严格一一对应`
+
+其它非深度学习库参照requirements.txt安装：
+```
+pip install -r requirements.txt
+```
+
+## 数据集
+暂无
+
+## 训练
+暂无
+
+## 推理
+```bash
+# 指定显卡
+export HIP_VISIBLE_DEVICE=0
+
+python inference.py --model_path /path/of/model
+```
+
+## result
+<div align=center>
+    <img src="./doc/result.png"/>
+</div>
+
+### 精度
+暂无
+
+## 应用场景
+### 算法类别
+多轮对话
+
+### 热点应用行业
+家居,教育,科研
+
+## 预训练权重
+- [Phi-3-mini-4k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-mini-4k-instruct)
+- [Phi-3-mini-128k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-mini-128k-instruct)
+- [Phi-3-small-8k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-small-8k-instruct)
+- [Phi-3-small-128k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-small-128k-instruct)
+- [Phi-3-medium-4k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-medium-4k-instruct)
+- [Phi-3-medium-128k-instruct](http://113.200.138.88:18080/aimodels/Phi-3-medium-128k-instruct)
+
+## 源码仓库及问题反馈
+- https://developer.hpccube.com/codes/modelzoo/phi-3_pytorch
+
+## 参考资料
+- https://huggingface.co/collections/microsoft/phi-3-6626e15e9585a200d2d761e3
+- https://azure.microsoft.com/en-us/blog/introducing-phi-3-redefining-whats-possible-with-slms/

docker/Dockerfile

+FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-ubuntu20.04-dtk24.04.1-py3.10
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inference.py

+import time
+import argparse
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+
+torch.random.manual_seed(0)
+
+def infer_hf(model_path, messages):
+    model = AutoModelForCausalLM.from_pretrained(
+        model_path,
+        device_map="cuda",
+        torch_dtype="auto",
+        trust_remote_code=True,
+    )
+
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    pipe = pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer,
+    )
+
+    generation_args = {
+        "max_new_tokens": 600,
+        "return_full_text": False,
+        "temperature": 0.3,
+        "do_sample": False,
+    }
+
+    start_time = time.time()
+    output = pipe(messages, **generation_args)
+    print("total infer time", time.time() - start_time)
+    print("output", output[0]['generated_text'])
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--model_path', default="/home/checkpoints/Phi-3-mini-128k-instruct/")
+    args = parser.parse_args()
+    return args
+
+
+if __name__ == "__main__":
+    args = parse_args()
+    messages = [
+        {"role": "system", "content": "You are a helpful AI assistant."},
+        {"role": "user", "content": "Can you provide ways to eat combinations of bananas and dragonfruits?"},
+        {"role": "assistant", "content": "Sure! Here are some ways to eat bananas and dragonfruits together: 1. Banana and dragonfruit smoothie: Blend bananas and dragonfruits together with some milk and honey. 2. Banana and dragonfruit salad: Mix sliced bananas and dragonfruits together with some lemon juice and honey."},
+        {"role": "user", "content": "What about solving an 2x + 3 = 7 equation?"},
+    ]
+
+    infer_hf(args.model_path, messages)

model.properties

+# 模型唯一标识
+modelCode=834
+# 模型名称
+modelName=phi-3_pytorch
+# 模型描述
+modelDescription=Phi-3模型是目前功能最强大、性价比最高的小型语言模型(SLM)，在各种语言、推理、编码和数学基准测试中，其表现优于同等规模和下一个规模的模型。
+# 应用场景
+appScenario=推理,多轮对话,家居,教育,科研
+# 框架类型
+frameType=pytorch

requirements.txt

+transformers==4.40.0
+accelerate
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