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企业网站推广方案网络营销作业,百度app下载官方免费最新版,wordpress 页面路由,慧聪网de网站建设策略1. 软件下载安装 Miniconda Miniconda下载地址 选择对应的版本下载，此处下载如下版本 Python 3.10 conda 25.1.1 安装完成后，配置环境变量，打开cmd命令窗口验证 Python Python的版本为 3.10 PyTorch PyTorch下载地址 后面通过命令下…

1. 软件下载安装

Miniconda

Miniconda下载地址
选择对应的版本下载，此处下载如下版本
Python 3.10
conda 25.1.1
在这里插入图片描述
安装完成后，配置环境变量，打开cmd命令窗口验证
在这里插入图片描述

Python

Python的版本为 3.10
在这里插入图片描述

PyTorch

PyTorch下载地址
后面通过命令下载
在这里插入图片描述

2. 环境配置

2.1 系统环境变量配置

我的电脑–属性–高级系统设置–系统属性(高级)–环境变量
在这里插入图片描述

2.1.1 配置NVSMI_HOME

新建环境变量，点击确定
在这里插入图片描述

编辑Path，点击新建
在这里插入图片描述

增加NVSMI_HOME配置后，点击确定
在这里插入图片描述

2.1.2 配置miniconda

安装miniconda时若勾选添加到环境变量，则忽略该步骤
在这里插入图片描述
编辑环境变量，点击新建，添加miniconda的路径，最后点击确定
在这里插入图片描述

2.2 查看cuda版本

方式一：打开cmd窗口,查看cuda版本

C:\Users\Administrator>nvidia-smi

在这里插入图片描述

方式二： 打开NVIDIA控制面板

在这里插入图片描述

3. 创建虚拟环境及安装依赖

操作步骤

# python版本为3.10
conda create -n deepseek python=3.10
conda activate deepseek
# 安装deepseek-sdk
pip install deepseek-sdk
# 安装torch 对应cuda12.8版本
pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
# transformers
pip install transformers>=4.33 accelerate sentencepiece
pip install protobuf
# 检查
conda list

D:\AI>conda create -n deepseek python=3.10
Channels:- defaults
Platform: win-64
Collecting package metadata (repodata.json): done
Solving environment: done==> WARNING: A newer version of conda exists. <==current version: 25.1.1latest version: 25.3.0Please update conda by running$ conda update -n base -c defaults conda## Package Plan ##environment location: D:\AI\soft\miniconda\envs\deepseekadded / updated specs:- python=3.10The following packages will be downloaded:package                    |            build---------------------------|-----------------ca-certificates-2025.2.25  |       haa95532_0         130 KBopenssl-3.0.16             |       h3f729d1_0         7.8 MBxz-5.6.4                   |       h4754444_1         280 KB------------------------------------------------------------Total:         8.2 MBThe following NEW packages will be INSTALLED:bzip2              pkgs/main/win-64::bzip2-1.0.8-h2bbff1b_6ca-certificates    pkgs/main/win-64::ca-certificates-2025.2.25-haa95532_0libffi             pkgs/main/win-64::libffi-3.4.4-hd77b12b_1openssl            pkgs/main/win-64::openssl-3.0.16-h3f729d1_0pip                pkgs/main/win-64::pip-25.0-py310haa95532_0python             pkgs/main/win-64::python-3.10.16-h4607a30_1setuptools         pkgs/main/win-64::setuptools-75.8.0-py310haa95532_0sqlite             pkgs/main/win-64::sqlite-3.45.3-h2bbff1b_0tk                 pkgs/main/win-64::tk-8.6.14-h0416ee5_0tzdata             pkgs/main/noarch::tzdata-2025a-h04d1e81_0vc                 pkgs/main/win-64::vc-14.42-haa95532_4vs2015_runtime     pkgs/main/win-64::vs2015_runtime-14.42.34433-he0abc0d_4wheel              pkgs/main/win-64::wheel-0.45.1-py310haa95532_0xz                 pkgs/main/win-64::xz-5.6.4-h4754444_1zlib               pkgs/main/win-64::zlib-1.2.13-h8cc25b3_1Proceed ([y]/n)? yDownloading and Extracting Packages:Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
#     $ conda activate deepseek
#
# To deactivate an active environment, use
#
#     $ conda deactivateD:\AI>conda activate deepseek(deepseek) D:\AI>
(deepseek) D:\AI>pip install deepseek-sdk
Collecting deepseek-sdkDownloading deepseek_sdk-0.1.0-py3-none-any.whl.metadata (1.4 kB)
Collecting openai>=1.0.0 (from deepseek-sdk)Downloading openai-1.68.2-py3-none-any.whl.metadata (25 kB)
Collecting anyio<5,>=3.5.0 (from openai>=1.0.0->deepseek-sdk)Downloading anyio-4.9.0-py3-none-any.whl.metadata (4.7 kB)
Collecting distro<2,>=1.7.0 (from openai>=1.0.0->deepseek-sdk)Downloading distro-1.9.0-py3-none-any.whl.metadata (6.8 kB)
Collecting httpx<1,>=0.23.0 (from openai>=1.0.0->deepseek-sdk)Downloading httpx-0.28.1-py3-none-any.whl.metadata (7.1 kB)
Collecting jiter<1,>=0.4.0 (from openai>=1.0.0->deepseek-sdk)Downloading jiter-0.9.0-cp310-cp310-win_amd64.whl.metadata (5.3 kB)
Collecting pydantic<3,>=1.9.0 (from openai>=1.0.0->deepseek-sdk)Downloading pydantic-2.10.6-py3-none-any.whl.metadata (30 kB)
Collecting sniffio (from openai>=1.0.0->deepseek-sdk)Downloading sniffio-1.3.1-py3-none-any.whl.metadata (3.9 kB)
Collecting tqdm>4 (from openai>=1.0.0->deepseek-sdk)Downloading tqdm-4.67.1-py3-none-any.whl.metadata (57 kB)
Collecting typing-extensions<5,>=4.11 (from openai>=1.0.0->deepseek-sdk)Downloading typing_extensions-4.12.2-py3-none-any.whl.metadata (3.0 kB)
Collecting exceptiongroup>=1.0.2 (from anyio<5,>=3.5.0->openai>=1.0.0->deepseek-sdk)Downloading exceptiongroup-1.2.2-py3-none-any.whl.metadata (6.6 kB)
Collecting idna>=2.8 (from anyio<5,>=3.5.0->openai>=1.0.0->deepseek-sdk)Downloading idna-3.10-py3-none-any.whl.metadata (10 kB)
Collecting certifi (from httpx<1,>=0.23.0->openai>=1.0.0->deepseek-sdk)Downloading certifi-2025.1.31-py3-none-any.whl.metadata (2.5 kB)
Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai>=1.0.0->deepseek-sdk)Downloading httpcore-1.0.7-py3-none-any.whl.metadata (21 kB)
Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai>=1.0.0->deepseek-sdk)Downloading h11-0.14.0-py3-none-any.whl.metadata (8.2 kB)
Collecting annotated-types>=0.6.0 (from pydantic<3,>=1.9.0->openai>=1.0.0->deepseek-sdk)Downloading annotated_types-0.7.0-py3-none-any.whl.metadata (15 kB)
Collecting pydantic-core==2.27.2 (from pydantic<3,>=1.9.0->openai>=1.0.0->deepseek-sdk)Downloading pydantic_core-2.27.2-cp310-cp310-win_amd64.whl.metadata (6.7 kB)
Collecting colorama (from tqdm>4->openai>=1.0.0->deepseek-sdk)Downloading colorama-0.4.6-py2.py3-none-any.whl.metadata (17 kB)
Downloading deepseek_sdk-0.1.0-py3-none-any.whl (2.4 kB)
Downloading openai-1.68.2-py3-none-any.whl (606 kB)---------------------------------------- 606.1/606.1 kB 99.1 kB/s eta 0:00:00
Downloading anyio-4.9.0-py3-none-any.whl (100 kB)
Downloading distro-1.9.0-py3-none-any.whl (20 kB)
Downloading httpx-0.28.1-py3-none-any.whl (73 kB)
Downloading httpcore-1.0.7-py3-none-any.whl (78 kB)
Downloading jiter-0.9.0-cp310-cp310-win_amd64.whl (208 kB)
Downloading pydantic-2.10.6-py3-none-any.whl (431 kB)
Downloading pydantic_core-2.27.2-cp310-cp310-win_amd64.whl (2.0 MB)---------------------------------------- 2.0/2.0 MB 79.5 kB/s eta 0:00:00
Downloading sniffio-1.3.1-py3-none-any.whl (10 kB)
Downloading tqdm-4.67.1-py3-none-any.whl (78 kB)
Downloading typing_extensions-4.12.2-py3-none-any.whl (37 kB)
Downloading annotated_types-0.7.0-py3-none-any.whl (13 kB)
Downloading exceptiongroup-1.2.2-py3-none-any.whl (16 kB)
Downloading idna-3.10-py3-none-any.whl (70 kB)
Downloading certifi-2025.1.31-py3-none-any.whl (166 kB)
Downloading colorama-0.4.6-py2.py3-none-any.whl (25 kB)
Downloading h11-0.14.0-py3-none-any.whl (58 kB)
Installing collected packages: typing-extensions, sniffio, jiter, idna, h11, exceptiongroup, distro, colorama, certifi, annotated-types, tqdm, pydantic-core, httpcore, anyio, pydantic, httpx, openai, deepseek-sdk
Successfully installed annotated-types-0.7.0 anyio-4.9.0 certifi-2025.1.31 colorama-0.4.6 deepseek-sdk-0.1.0 distro-1.9.0 exceptiongroup-1.2.2 h11-0.14.0 httpcore-1.0.7 httpx-0.28.1 idna-3.10 jiter-0.9.0 openai-1.68.2 pydantic-2.10.6 pydantic-core-2.27.2 sniffio-1.3.1 tqdm-4.67.1 typing-extensions-4.12.2(deepseek) D:\AI\soft>pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
Looking in indexes: https://download.pytorch.org/whl/nightly/cu128
Collecting torchDownloading https://download.pytorch.org/whl/nightly/cu128/torch-2.8.0.dev20250321%2Bcu128-cp310-cp310-win_amd64.whl.metadata (29 kB)
Collecting torchvisionDownloading https://download.pytorch.org/whl/nightly/cu128/torchvision-0.22.0.dev20250321%2Bcu128-cp310-cp310-win_amd64.whl.metadata (6.3 kB)
Collecting torchaudioDownloading https://download.pytorch.org/whl/nightly/cu128/torchaudio-2.6.0.dev20250321%2Bcu128-cp310-cp310-win_amd64.whl.metadata (6.8 kB)
Collecting filelock (from torch)Downloading https://download.pytorch.org/whl/nightly/filelock-3.16.1-py3-none-any.whl (16 kB)
Requirement already satisfied: typing-extensions>=4.10.0 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from torch) (4.12.2)
Collecting sympy>=1.13.3 (from torch)Downloading https://download.pytorch.org/whl/nightly/sympy-1.13.3-py3-none-any.whl (6.2 MB)---------------------------------------- 6.2/6.2 MB 3.7 MB/s eta 0:00:00
Collecting networkx (from torch)Downloading https://download.pytorch.org/whl/nightly/networkx-3.4.2-py3-none-any.whl (1.7 MB)---------------------------------------- 1.7/1.7 MB 3.2 MB/s eta 0:00:00
Collecting jinja2 (from torch)Downloading https://download.pytorch.org/whl/nightly/jinja2-3.1.4-py3-none-any.whl (133 kB)
Collecting fsspec (from torch)Downloading https://download.pytorch.org/whl/nightly/fsspec-2024.10.0-py3-none-any.whl (179 kB)
Collecting numpy (from torchvision)Downloading https://download.pytorch.org/whl/nightly/numpy-2.1.2-cp310-cp310-win_amd64.whl (12.9 MB)---------------------------------------- 12.9/12.9 MB 3.5 MB/s eta 0:00:00
Collecting torchDownloading https://download.pytorch.org/whl/nightly/cu128/torch-2.8.0.dev20250320%2Bcu128-cp310-cp310-win_amd64.whl.metadata (29 kB)
Collecting pillow!=8.3.*,>=5.3.0 (from torchvision)Downloading https://download.pytorch.org/whl/nightly/pillow-11.0.0-cp310-cp310-win_amd64.whl (2.6 MB)---------------------------------------- 2.6/2.6 MB 4.2 MB/s eta 0:00:00
Collecting mpmath<1.4,>=1.1.0 (from sympy>=1.13.3->torch)Downloading https://download.pytorch.org/whl/nightly/mpmath-1.3.0-py3-none-any.whl (536 kB)---------------------------------------- 536.2/536.2 kB 4.4 MB/s eta 0:00:00
Collecting MarkupSafe>=2.0 (from jinja2->torch)Downloading https://download.pytorch.org/whl/nightly/MarkupSafe-2.1.5-cp310-cp310-win_amd64.whl (17 kB)
Downloading https://download.pytorch.org/whl/nightly/cu128/torchvision-0.22.0.dev20250321%2Bcu128-cp310-cp310-win_amd64.whl (7.6 MB)---------------------------------------- 7.6/7.6 MB 4.2 MB/s eta 0:00:00
Downloading https://download.pytorch.org/whl/nightly/cu128/torch-2.8.0.dev20250320%2Bcu128-cp310-cp310-win_amd64.whl (3327.8 MB)---------------------------------------- 3.3/3.3 GB 2.7 MB/s eta 0:00:00
Downloading https://download.pytorch.org/whl/nightly/cu128/torchaudio-2.6.0.dev20250321%2Bcu128-cp310-cp310-win_amd64.whl (4.7 MB)---------------------------------------- 4.7/4.7 MB 4.9 MB/s eta 0:00:00
Installing collected packages: mpmath, sympy, pillow, numpy, networkx, MarkupSafe, fsspec, filelock, jinja2, torch, torchvision, torchaudio
Successfully installed MarkupSafe-2.1.5 filelock-3.16.1 fsspec-2024.10.0 jinja2-3.1.4 mpmath-1.3.0 networkx-3.4.2 numpy-2.1.2 pillow-11.0.0 sympy-1.13.3 torch-2.8.0.dev20250320+cu128 torchaudio-2.6.0.dev20250321+cu128 torchvision-0.22.0.dev20250321+cu128(deepseek) D:\AI\>

4. 模型下载

DeepSeek模型下载地址
此处下载DeepSeek-R1-Distill-Qwen-7B版本
在这里插入图片描述
本地创建文件夹，将下载的文件全部复制到文件夹下

5. 测试

创建测试目录，在目录下创建脚本文件test.py，脚本内容如

#使用transformer加载模型
from transformers import AutoTokenizer, AutoModelForCausalLM
#加载本地模型路径
model_path = "D:\AI\models"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path,device_map="balanced_low_0",torch_dtype='float16'
)
prompt = "请给一个deepseek的搭建步骤"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs,max_new_tokens=128,do_sample=True,temperature=0.7
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

执行测试脚本

# 激活deepseek环境
conda activate deepseek
cd D:\AI\scripts
# 执行脚本
python test.py
# 测试完成后退出
#conda deactivate

长时间等待的结果
在这里插入图片描述

CPU、内存和GPU

在这里插入图片描述

6. 其他模型

6.1 下载deepseek-llm-7b-chat模型

# 1.安装modelscope
(deepseek) D:\AI>pip install modelscope
# 2.下载模型文件
(deepseek) D:\AI>modelscope download --model deepseek-ai/deepseek-llm-7b-chat

(deepseek) D:\AI\scripts>pip install modelscope
Collecting modelscopeDownloading modelscope-1.24.0-py3-none-any.whl.metadata (39 kB)
Requirement already satisfied: requests>=2.25 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from modelscope) (2.32.3)
Requirement already satisfied: tqdm>=4.64.0 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from modelscope) (4.67.1)
Requirement already satisfied: urllib3>=1.26 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from modelscope) (2.3.0)
Requirement already satisfied: charset-normalizer<4,>=2 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from requests>=2.25->modelscope) (3.4.1)
Requirement already satisfied: idna<4,>=2.5 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from requests>=2.25->modelscope) (3.10)
Requirement already satisfied: certifi>=2017.4.17 in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from requests>=2.25->modelscope) (2025.1.31)
Requirement already satisfied: colorama in d:\ai\soft\miniconda\envs\deepseek\lib\site-packages (from tqdm>=4.64.0->modelscope) (0.4.6)
Downloading modelscope-1.24.0-py3-none-any.whl (5.9 MB)---------------------------------------- 5.9/5.9 MB 42.8 kB/s eta 0:00:00
Installing collected packages: modelscope
Successfully installed modelscope-1.24.0(deepseek) D:\AI\scripts>(deepseek) D:\AI\scripts>modelscope download --model deepseek-ai/deepseek-llm-7b-chat
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator\.cache\modelscope\hub\models\deepseek-ai\deepseek-llm-7b-chat
Downloading [README.md]: 100%|███████████████████████████████████████████████████████████████████████████| 3.16k/3.16k [00:00<00:00, 8.49kB/s]
Downloading [configuration.json]: 100%|██████████████████████████████████████████████████████████████████████| 73.0/73.0 [00:00<00:00, 176B/s]
Downloading [generation_config.json]: 100%|████████████████████████████████████████████████████████████████████| 181/181 [00:00<00:00, 387B/s]
Downloading [pytorch_model.bin.index.json]: 100%|████████████████████████████████████████████████████████| 21.9k/21.9k [00:00<00:00, 49.1kB/s]
Downloading [config.json]: 100%|█████████████████████████████████████████████████████████████████████████████| 594/594 [00:00<00:00, 1.26kB/s]
Downloading [tokenizer_config.json]: 100%|███████████████████████████████████████████████████████████████| 1.25k/1.25k [00:00<00:00, 2.21kB/s]
Downloading [tokenizer.json]: 100%|██████████████████████████████████████████████████████████████████████| 4.40M/4.40M [00:03<00:00, 1.33MB/s]
Processing 9 items:  78%|███████████████████████████████████████████████████████████████▊                  | 7.00/9.00 [00:03<00:01, 1.61it/s]
Downloading [tokenizer_config.json]:   0%|                                                                        | 0.00/1.25k [00:00<?, ?B/s]Downloading [pytorch_model-00001-of-00002.bin]:   0%|                                                  | 6.00M/9.28G [00:03<1:08:33, 2.42MB/s]
Downloading [pytorch_model-00001-of-00002.bin]:   1%|▌                                                    | 110M/9.28G [00:42<55:11, 2.98MB/s]
Downloading [pytorch_model-00002-of-00002.bin]:   0%|                                                    | 4.00M/3.59G [00:03<52:32, 1.22MB/s]
Downloading [pytorch_model-00002-of-00002.bin]:   2%|█▏                                                  | 88.0M/3.59G [00:42<42:44, 1.47MB/s]
Downloading [tokenizer.json]: 100%|██████████████████████████████████████████████████████████████████████| 4.40M/4.40M [00:03<00:00, 1.49MB/s]

6.2 修改脚本中模型的路径

下载完成后，默认在C:\Users\Administrator.cache\modelscope\hub\models\deepseek-ai目录下，将deepseek-llm-7b-chat文件夹复制到自定义的文件夹model下。
修改test.py脚本

#使用transformer加载模型
from transformers import AutoTokenizer, AutoModelForCausalLM
#加载本地模型路径
model_path = "D:\AI\model\deepseek-llm-7b-chat"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path,device_map="balanced_low_0",torch_dtype='float16'
)
prompt = "请给一个deepseek的搭建步骤"
inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs,max_new_tokens=1000,do_sample=True,temperature=0.8
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

执行脚本

# 激活deepseek环境
conda activate deepseek
cd D:\AI\scripts
# 执行脚本
python test.py

在这里插入图片描述

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