1. 在Linux服務器上部署DeepSeek模型
要在 Linux 上通過 Ollama 安裝和使用模型,您可以按照以下步驟進行操作:
步驟 1:安裝 Ollama
-
安裝 Ollama:
使用以下命令安裝 Ollama:curl -sSfL https://ollama.com/download.sh | sh
-
驗證安裝:
安裝完成后,您可以通過以下命令驗證 Ollama 是否安裝成功:ollama --version
步驟 2:下載模型
ollama run deepseek-r1:32b
這將下載并啟動DeepSeek R1 32B模型。
DeepSeek R1 蒸餾模型列表
模型名稱 | 參數量 | 基礎架構 | 適用場景 |
---|---|---|---|
DeepSeek-R1-Distill-Qwen-1.5B | 1.5B | Qwen2.5 | 適合移動設備或資源受限的終端 |
DeepSeek-R1-Distill-Qwen-7B | 7B | Qwen2.5 | 適合普通文本生成工具 |
DeepSeek-R1-Distill-Llama-8B | 8B | Llama3.1 | 適合小型企業日常文本處理 |
DeepSeek-R1-Distill-Qwen-14B | 14B | Qwen2.5 | 適合桌面級應用 |
DeepSeek-R1-Distill-Qwen-32B | 32B | Qwen2.5 | 適合專業領域知識問答系統 |
DeepSeek-R1-Distill-Llama-70B | 70B | Llama3.3 | 適合科研、學術研究等高要求場景 |
RTX 4090 顯卡顯存為 24GB,32B 模型在 4-bit 量化下約需 22GB 顯存,適合該硬件。32B 模型在推理基準測試中表現優異,接近 70B 模型的推理能力,但對硬件資源需求更低。
步驟 3:運行模型
通過上面的步驟,已經可以直接在 Linux服務器通過命令行的形式使用Deepseek了。但是不夠友好,下面介紹更方便的形式。
2. 在linux服務器配置Ollama服務
1. 設置Ollama服務配置
設置OLLAMA_HOST=0.0.0.0環境變量,這使得Ollama服務能夠監聽所有網絡接口,從而允許遠程訪問。
sudo vi /etc/systemd/system/ollama.service
[Unit]
Description=Ollama Service
After=network-online.target[Service]
ExecStart=/usr/local/bin/ollama serve
User=ollama
Group=ollama
Restart=always
RestartSec=3
Environment="OLLAMA_HOST=0.0.0.0"
Environment="PATH=/usr/local/cuda/bin:/home/bytedance/miniconda3/bin:/home/bytedance/miniconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin"[Install]
WantedBy=default.target
2. 重新加載并重啟Ollama服務
sudo systemctl daemon-reload
sudo systemctl restart ollama
- 驗證Ollama服務是否正常運行
運行以下命令,確保Ollama服務正在監聽所有網絡接口:
sudo netstat -tulpn | grep ollama
您應該看到類似以下的輸出,表明Ollama服務正在監聽所有網絡接口(0.0.0.0):
tcp 0 0 0.0.0.0:11434 0.0.0.0:* LISTEN - ollama
4. 配置防火墻以允許遠程訪問
為了確保您的Linux服務器允許從外部訪問Ollama服務,您需要配置防火墻以允許通過端口11434的流量。
sudo ufw allow 11434/tcp
sudo ufw reload
5. 驗證防火墻規則
確保防火墻規則已正確添加,并且端口11434已開放。您可以使用以下命令檢查防火墻狀態:
sudo ufw status
狀態: 激活至 動作 來自
- -- --
22/tcp ALLOW Anywhere
11434/tcp ALLOW Anywhere
22/tcp (v6) ALLOW Anywhere (v6)
11434/tcp (v6) ALLOW Anywhere (v6)
6. 測試遠程訪問
在完成上述配置后,您可以通過遠程設備(如Mac)測試對Ollama服務的訪問。
在遠程設備上測試連接:
在Mac上打開終端,運行以下命令以測試對Ollama服務的連接:
curl http://10.70.83.38:11434/api/version
顯示
{"version":"0.5.7"}
測試問答
(base) ? ~ curl -X POST http://10.70.83.38:11434/api/generate \-H "Content-Type: application/json" \-d '{"model": "deepseek-r1:32b", "prompt": "你是誰?"}'
顯示
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.118616168Z","response":"\u003cthink\u003e","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.150938966Z","response":"\n\n","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.175255854Z","response":"\u003c/think\u003e","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.199509353Z","response":"\n\n","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.223657359Z","response":"您好","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.24788375Z","response":"!","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.272068174Z","response":"我是","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.296163417Z","response":"由","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.320515728Z","response":"中國的","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.344646528Z","response":"深度","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.36880216Z","response":"求","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.393006489Z","response":"索","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.417115966Z","response":"(","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.441321254Z","response":"Deep","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.465439117Z","response":"Seek","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.489619415Z","response":")","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.51381827Z","response":"公司","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.538012781Z","response":"開發","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.562186246Z","response":"的","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.586331325Z","response":"智能","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.610539651Z","response":"助手","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.634769989Z","response":"Deep","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.659134003Z","response":"Seek","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.683523205Z","response":"-R","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.70761762Z","response":"1","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.731953604Z","response":"。","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.756135462Z","response":"如","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.783480232Z","response":"您","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.807766337Z","response":"有任何","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.831964079Z","response":"任何","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.856229156Z","response":"問題","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.880487159Z","response":",","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.904710537Z","response":"我會","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.929026993Z","response":"盡","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.953239249Z","response":"我","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:15.977496819Z","response":"所能","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:16.001763128Z","response":"為您提供","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:16.026068523Z","response":"幫助","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:16.050242581Z","response":"。","done":false}
{"model":"deepseek-r1:32b","created_at":"2025-02-06T00:47:16.074454593Z","response":"","done":true,"done_reason":"stop","context":[151644,105043,100165,30,151645,151648,271,151649,198,198,111308,6313,104198,67071,105538,102217,30918,50984,9909,33464,39350,7552,73218,100013,9370,100168,110498,33464,39350,12,49,16,1773,29524,87026,110117,99885,86119,3837,105351,99739,35946,111079,113445,100364,1773],"total_duration":3872978599,"load_duration":2811407308,"prompt_eval_count":6,"prompt_eval_duration":102000000,"eval_count":40,"eval_duration":958000000}
通過上述步驟,已經成功在Linux服務器上配置了Ollama服務,并通過Mac遠程訪問了DeepSeek模型。接下來,將介紹如何在Mac上安裝Web UI,以便更方便地與模型進行交互。
3. 在Mac上安裝Web UI
為了更方便地與遠程Linux服務器上的DeepSeek模型進行交互,可以在Mac上安裝一個Web UI工具。這里我們推薦使用 Open Web UI,它是一個基于Web的界面,支持多種AI模型,包括Ollama。
1. 通過conda安裝open-webui
打開終端,運行以下命令創建一個新的conda環境,并指定Python版本為3.11:
conda create -n open-webui-env python=3.11
conda activate open-webui-env
pip install open-webui
2. 啟動open-webui
open-webui serve
3. 瀏覽器訪問
http://localhost:8080/
- 使用管理員身份(第一個注冊用戶)登錄
- 在Open webui界面中,依次點擊“展開左側欄”(左上角三道杠)–>“頭像”(左下角)–>管理員面板–>設置(上側)–>外部連接
- 在外部連接的Ollama API一欄將switch開關打開,在欄中填上http://10.70.83.38:11434(這是我的服務器地址)
- 點擊右下角“保存”按鈕
- 點擊“新對話”(左上角),確定是否正確刷出模型列表,如果正確刷出,則設置完畢。
4. 愉快的使用本地deepseek模型