update codes

.gitignore

+experiments/*
+results/*
+tb_logger/*
+wandb/*
+tmp/*
+modify_model.py
+hat/version.py
+
+*.DS_Store
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/

README.md

-# DeepSeek-coder-V2_pytorch
+# DeepSeek-Coder
+DeepSeek Coder V2系列基于Deepseek-V2改进而来，有16B和236B两个版本。
+## 论文
+`DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence`<br>
+[deepseek-coder-V2](https://arxiv.org/pdf/2406.11931)
 
+## 模型结构
+DeepSeek-Coder-V2模型采用和Deepseek-V2同样的MoE架构
+<div align=center>
+    <img src="./assets/model_framework.png"/>
+</div>
+
+## 算法原理
+DeepSeek-V2对模型框架进行了全方位的创新，提出了媲美MHA的MLA（Multi-head Latent Attention）架构，大幅减少计算量和推理显存；自研Sparse结构DeepSeekMoE进一步将计算量降低到极致，两者结合最终实现模型性能跨级别的提升。
+## 环境配置
+-v 路径、docker_name和imageID根据实际情况修改
+
+### Docker（方法一）
+
+```bash
+docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
+docker run -it -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro --shm-size=80G --privileged=true --device=/dev/kfd --device=/dev/dri/ --group-add video --name docker_name imageID bash
+
+cd /your_code_path/deepseek-coder-v2_pytorch
+pip install -r requirements.txt
+pip install -U huggingface_hub hf_transfer
+export HF_ENDPOINT=https://hf-mirror.com
+```
+
+### Dockerfile（方法二）
+
+```bash
+cd docker
+docker build --no-cache -t deepseek-coder-v2:latest .
+docker run -it -v /path/your_code_data/:/path/your_code_data/ -v /opt/hyhal/:/opt/hyhal/:ro --shm-size=80G --privileged=true --device=/dev/kfd --device=/dev/dri/ --group-add video --name docker_name imageID bash
+
+cd /your_code_path/deepseek-v2_pytorch
+pip install -r requirements.txt
+pip install -U huggingface_hub hf_transfer
+export HF_ENDPOINT=https://hf-mirror.com
+
+```
+
+### 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
+python: python3.10
+torch: 2.1.0
+```
+`Tips：以上dtk驱动、python、torch等DCU相关工具版本需要严格一一对应`
+
+其它非深度学习库安装方式如下：
+```bash
+pip install -r requirements.txt
+pip install -U huggingface_hub hf_transfer
+export HF_ENDPOINT=https://hf-mirror.com
+```
+
+## 数据集
+暂无
+
+## 训练
+暂无
+
+## 推理
+基于Huggingface's Transformers进行推理.<br>
+模型下载后 默认需存放至weights文件夹中<br>
+也可自行更改 inference.py文件中的 model_name 参数<br>
+模型下载地址[快速下载](http://113.200.138.88:18080/aimodels/deepseek-ai) [官方下载](http://113.200.138.88:18080/aimodels/deepseek-ai)
+```python
+HIP_VISIBLE_DEVICES=0 python inference.py
+```
+## Result
+prompt：write a quick sort algorithm in python.<br>
+<div align=center>
+    <img src="./assets/result.png"/>
+</div>
+
+### 精度
+暂无
+
+## 应用场景
+### 算法类别
+代码生成
+
+### 热点应用行业
+制造,能源,教育
+
+## 预训练权重
+模型目录结构如下：
+```bash
+# deepseek-coder-6.7b-instruct/
+├── config.json
+├── generation_config.json
+├── LICENSE
+├── model-00001-of-00002.safetensors
+├── model-00002-of-00002.safetensors
+├── model.safetensors.index.json
+├── pytorch_model-00001-of-00002.bin
+├── pytorch_model-00002-of-00002.bin
+├── pytorch_model.bin.index.json
+├── README.md
+├── tokenizer_config.json
+└── tokenizer.json
+```
+
+## 源码仓库及问题反馈
+- https://developer.hpccube.com/codes/modelzoo/deepseek-coder-v2_pytorch
+
+## 参考资料
+- https://github.com/deepseek-ai/DeepSeek-Coder-V2?tab=readme-ov-file
+- https://huggingface.co/deepseek-ai

docker/Dockerfile

+FROM image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
\ No newline at end of file

inference.py

+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import time
+tokenizer = AutoTokenizer.from_pretrained("./DeepSeek-Coder-V2-Lite-Instruct", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("./DeepSeek-Coder-V2-Lite-Instruct", trust_remote_code=True, torch_dtype=torch.bfloat16).cuda()
+messages=[
+    { 'role': 'user', 'content': "write a quick sort algorithm in python."}
+]
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+# tokenizer.eos_token_id is the id of <|EOT|> token
+outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
+print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
\ No newline at end of file

model.properties

+# 模型唯一标识
+modelCode=743
+# 模型名称
+modelName=deepseek-coder-v2_pytorch
+# 模型描述
+modelDescription=DeepSeek-Coder-V2代码生成方向大模型，支持338种编程语言
+# 应用场景
+appScenario=推理,训练,代码生成,制造,能源,教育
+# 框架类型
+frameType=pytorch

requirements.txt

+#torch>=2.0
+#tokenizers>=0.14.0
+#transformers==4.35.0
+#accelerate
+#deepspeed==0.12.2
+sympy==1.12
+pebble 
+timeout-decorator 
+accelerate
+attrdict
+tqdm
+datasets
+tensorboardX