How to Set Up and Use DeepSeek Locally?

Why Deploy DeepSeek Locally?

DeepSeek is a high-performance open-source large language model. Compared with online usage, setting up DeepSeek locally has the following advantages:

Privacy & Security: All data is stored locally, avoiding cloud uploads.
Offline Usage: You can run the AI model even without an internet connection.
High Flexibility: Freely adjust parameters and conduct secondary development.
Cost Control: No need for long-term paid APIs; run on your own hardware.

Prerequisites

Before setting up DeepSeek, make sure your computer meets the following requirements:

Operating System: Windows / macOS / Linux
Python: Recommended version 3.10+
GPU: NVIDIA GPU (recommended 8GB VRAM or more)
Dependencies: Git, pip, conda (optional)

Installation and Setup Steps

1. Clone the DeepSeek Repository


git clone https://github.com/deepseek-ai/DeepSeek.git
cd DeepSeek

2. Create a Python Environment and Install Dependencies


# Create a virtual environment with conda
conda create -n deepseek python=3.10 -y
conda activate deepseek

# Install dependencies
pip install -r requirements.txt

3. Download the DeepSeek Model

DeepSeek model files can be downloaded from Hugging Face or official links, for example:


# Example: DeepSeek-7B
git lfs install
git clone https://huggingface.co/deepseek-ai/deepseek-7b

4. Run the Model


python app.py --model ./deepseek-7b

Once started, you can access the locally deployed DeepSeek via http://localhost:8000.

Usage Example

Python Example


from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-7b")
model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-7b")

inputs = tokenizer("Hello, DeepSeek!", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0]))

FAQ

1. What if my GPU memory is insufficient?: You can use quantized models (int4/int8) or run on CPU, but performance will be reduced.
2. How to improve DeepSeek's Chinese support?: It is recommended to download a Chinese-optimized version, such as DeepSeek-CN.
3. How to use it in a web interface?: You can integrate it with text-generation-webui, which provides a more intuitive graphical interface.

Conclusion

This article provides a detailed guide on how to set up and use DeepSeek locally, covering environment preparation, dependency installation, model downloading, and testing. If you are interested in AI application development, data privacy, or offline large models, try running DeepSeek locally.

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