How to self-host DeepSeek-Coder with Hugging Face TGI as private AI

Run DeepSeek-Coder from DeepSeek as your own private, self-hosted AI. TGI runs the model on your own GPU server, and TypingMind gives you a full chat app on top of it. Your prompts stay on your servers, and there is no per-message cost.

About DeepSeek-Coder: DeepSeek Coder is a capable coding model trained on two trillion code and natural language tokens.

DeepSeek-Coder Overview

ModelDeepSeek-Coder
Made byDeepSeek
Runs onHugging Face TGI
Versionsdeepseek-coder-1.3b-instruct, deepseek-coder-6.7b-instruct, deepseek-coder-7b-instruct-v1.5, deepseek-coder-33b-instruct
Model weights2.7 GB to 66.7 GB
Minimum GPU1 × 16 GB GPU
Context window4K
LicenseDeepSeek License
AccessOpen to everyone
TGI model IDdeepseek-ai/deepseek-coder-7b-instruct-v1.5
Downloads on Hugging Face251.7K last month
Model iconGet the icon for TypingMind

Which version of DeepSeek-Coder should you pick?

Each version is a different size of DeepSeek-Coder. Bigger versions give better answers but need more GPU memory. Pick the biggest one that fits your GPUs.

Model IDParametersWeightsSuggested GPU
deepseek-ai/deepseek-coder-1.3b-instruct1.3B2.7 GB1 × 16 GB GPU
deepseek-ai/deepseek-coder-6.7b-instruct6.7B13.5 GB1 × 24 GB GPU
deepseek-ai/deepseek-coder-7b-instruct-v1.5used in this guide6.9B13.8 GB1 × 24 GB GPU
deepseek-ai/deepseek-coder-33b-instruct33.3B66.7 GB2 × 80 GB GPUs

Suggested GPU is a rough guide: the full-precision weights plus about 20% and 2 GB for chats. Longer context windows and more users need more. A 24 GB GPU is an NVIDIA L4, A10G, or RTX 4090, and an 80 GB GPU is an A100 or H100.

Run DeepSeek-Coder with TGI

The steps below use deepseek-ai/deepseek-coder-7b-instruct-v1.5, a version that fits 1 × 24 GB GPU. Swap in another model ID from the table if you want a smaller or bigger one.

Before you start

  • You need a Linux server with an NVIDIA GPU, Docker, and the NVIDIA Container Toolkit. A cloud GPU server works too. TGI doesn't run on a Mac; on a laptop, use Ollama or LM Studio.
  • Hugging Face has archived TGI. It still works, but it no longer gets updates, and new model families go to vLLM and SGLang instead.
I

Get DeepSeek-Coder from Hugging Face

Open deepseek-ai/deepseek-coder-7b-instruct-v1.5 on Hugging Face. The model ID is the part after huggingface.co/, and you can copy it with the button next to the name. The text-generation-inference tag means the model works with TGI.

Hugging Face model page with the model ID, copy button, and text-generation-inference tag
Copy the model ID from the model page (example with Qwen/Qwen2.5-7B-Instruct)

DeepSeek-Coder is open to everyone, so you don't need a Hugging Face account or token to download it.

II

Start DeepSeek-Coder with TGI

On your GPU server (1 × 24 GB GPU or more), run:

docker run -d --rm --name tgi --gpus all --shm-size 1g \
  -p 127.0.0.1:8080:80 \
  -v $PWD/data:/data \
  ghcr.io/huggingface/text-generation-inference:3.3.5 \
  --model-id deepseek-ai/deepseek-coder-7b-instruct-v1.5 \
  --num-shard 1 \
  --cors-allow-origin https://www.typingmind.com
  • -d keeps TGI running after you close the terminal.
  • -p 127.0.0.1:8080:80 serves TGI on port 8080 of your server, for connections from the server itself only. The SSH tunnel in step III is one of them.
  • -v $PWD/data:/data keeps the downloaded model, so the next start is fast.
  • --num-shard 1 keeps the model on one GPU, even if your server has more.
  • --cors-allow-origin https://www.typingmind.com lets only the TypingMind web app call TGI from a browser, not other websites you visit.

The first start downloads 13.8 GB of model weights, so it can take a while. Follow along with:

docker logs -f tgi

TGI is ready when the log prints Connected. Press Ctrl+C to stop following the log, then check it with:

curl http://localhost:8080/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{"model": "tgi", "messages": [{"role": "user", "content": "Say hi"}]}'

You should get a JSON reply with the model's answer.

III

Connect your computer to TGI

TypingMind runs on https://, so your browser blocks calls to a plain http:// server, unless the server is at localhost. An SSH tunnel makes TGI show up at localhost:8080 on your computer. On your computer, run:

ssh -N -L 8080:localhost:8080 user@your-gpu-server

Replace user@your-gpu-server with how you log in to the server, and keep this terminal open while you chat. Skip this step if TGI runs on the computer you use for TypingMind.

IV

Add DeepSeek-Coder to TypingMind

Open www.typingmind.com in your browser. Use the web version: the TypingMind Mac app and the Setapp version block plain http:// addresses like TGI's.

Click Models in the left sidebar, then Add custom model.

Fill in the form:

Namedeepseek-coder-7b-instruct-v1.5 (TGI)or any name you like
Model IDdeepseek-ai/deepseek-coder-7b-instruct-v1.5
Context Length4096lower it if TGI rejects long chats
API TypeOpenAI Chat Completions API
Endpoint URLhttp://localhost:8080/v1/chat/completions
Authentication TypeNo authentication
TypingMind Add Custom Model form filled in for deepseek-ai/deepseek-coder-7b-instruct-v1.5 running on TGIdeepseek-coder-7b-instruct-v1.5 (TGI)deepseek-ai/deepseek-coder-7b-instruct-v1.54096http://localhost:8080/v1/chat/completions
The custom model form for deepseek-ai/deepseek-coder-7b-instruct-v1.5

Open the Capabilities tab and turn off Auto check capabilities on save, so TypingMind keeps the features you set below.

Then set the features for DeepSeek-Coder:

  • Support System Role: on
  • Support Streaming Output: on
  • Support Plugins: off
  • Support Image Input: off
  • Support PDF Input: off
  • Support External Image URLs: off
  • Support Thinking: off
  • Support Prompt Caching: off

Click Test & Save. If your browser asks to let www.typingmind.com access other apps and services on this device, click Allow. This lets the page reach TGI at localhost.

V

Chat with DeepSeek-Coder in TypingMind

Pick deepseek-coder-7b-instruct-v1.5 (TGI) in the model menu under the chat box and say hi. Replies come straight from your own GPU server.

Chatting with DeepSeek-Coder running on TGI on your own GPU server in TypingMinddeepseek-coder-7b-instruct-v1.5 (TGI)
A private chat with DeepSeek-Coder on your own GPU server

You can now use your private AI with TypingMind's chat features: prompts, AI agents, projects, and switching between your self-hosted model and cloud models in the same chat.

Tips and troubleshooting

1. "Could not connect to the API (code: 1)"

TypingMind can't reach TGI. Check these in order:

  • The SSH tunnel is still open. If you closed its terminal, run the tunnel command from step III again.
  • TGI is still running on the server: docker ps should list tgi. If it's gone, run the command from step II again.
  • TGI answers on the server. Run this on the server:
curl http://localhost:8080/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -d '{"model": "tgi", "messages": [{"role": "user", "content": "Say hi"}]}'
  • You clicked Allow when the browser asked about accessing apps on this device.
  • You're using TypingMind in the browser, not the Mac or Setapp app.

2. TGI stops with "CUDA out of memory"

The model is too big for your GPU. Pick a smaller size from the size table, or add GPUs and split the model across them with --num-shard.

3. Long chats fail with a token limit error

TGI fits the context window to your GPU memory. Lower Context Length in the TypingMind model settings.

4. The first message of a new chat seems stuck

TypingMind writes a title for each new chat. If the title is made by the same model, your reply can wait behind the title. Go to Settings → Internal prompts, open Advanced Settings under Auto generate title for new chats, and pick another model for title generation, or turn auto titles off.

5. See what TGI is doing

Watch every request as it happens:

docker logs -f tgi

TGI runs one model at a time. To switch models, stop it with docker stop tgi and start it again with a new --model-id.

Frequently Asked Questions

Is DeepSeek-Coder free to run with TGI?

Yes. TGI is free and open source, and DeepSeek-Coder is an open model. DeepSeek-Coder is open to everyone on Hugging Face, so you don't need a token to download it. You only pay for your own GPU server, with no per-message cost.

Is DeepSeek-Coder private when I run it with TGI?

Yes. Your messages go from your browser to TGI on your own server, not to an AI company. TypingMind keeps your chat history in your browser. If you turn on Cloud Sync, your chats are also backed up to TypingMind's cloud.

How much GPU memory do I need for DeepSeek-Coder?

The smallest version, deepseek-ai/deepseek-coder-1.3b-instruct, needs about 1 × 16 GB GPU. The version used in this guide, deepseek-ai/deepseek-coder-7b-instruct-v1.5, needs about 1 × 24 GB GPU.

Which Model ID do I use in TypingMind?

TGI serves one model per server, so it does not use the Model ID to pick a model. Use the Hugging Face model ID, for example deepseek-ai/deepseek-coder-7b-instruct-v1.5, so you can tell your models apart in TypingMind.

Can DeepSeek-Coder use TypingMind plugins?

DeepSeek-Coder's chat template doesn't list tool use, so keep Support Plugins off. Pick a model with tool calling if you need plugins.

Can DeepSeek-Coder read images?

No. DeepSeek-Coder is a text model, so keep Support Image Input off.

Can I run TGI on my Mac or laptop?

Not really. TGI is built for NVIDIA GPUs, and Docker on a Mac cannot use the Mac's GPU. On a Mac or a laptop, use Ollama or LM Studio instead.

Does TypingMind run locally?

TypingMind runs in your browser at www.typingmind.com, and your chats are stored locally in your browser by default. When you chat with a self-hosted model, your messages go straight from your browser to the model on your own GPU server, not through TypingMind’s servers. If you turn on Cloud Sync, your chats are also backed up to TypingMind’s cloud.

Can I self-host TypingMind?

Yes. To self-host TypingMind for your team or company, use the self-hosted version of TypingMind Teams. You run it on your own servers next to your self-hosted models, so chats, users, and settings stay inside your own infrastructure. Contact our sales team to get started.

More models for Hugging Face TGI