DeepSeek Coder: Get Started

What is DeepSeek Coder?

DeepSeek Coder is an open-source code language model developed by DeepSeek AI, designed to assist developers by generating code snippets, offering code completions, and providing solutions across various programming languages. With advanced AI-driven capabilities, DeepSeek Coder significantly enhances coding efficiency, reduces development time, and supports multilingual development.
This model has been trained on a vast dataset comprising 87% code and 13% natural language in both English and Chinese. The inclusion of multilingual support ensures that DeepSeek Coder is versatile enough to be used by developers working in different languages.

Key Features of DeepSeek Coder

1. Diverse Model Sizes

DeepSeek Coder is available in multiple configurations, including:

• 1.3 billion parameters


• 5.7 billion parameters


• 6.7 billion parameters


• 33 billion parameters

This range of model sizes allows developers to select the most appropriate version based on their computational resources and specific project needs.

2. Extended Context Window

With a context window of up to 16,000 tokens, DeepSeek Coder supports:

• Project-level code completion


• Code infilling capabilities


• Handling larger codebases efficiently


• Providing comprehensive assistance for intricate development tasks

3. Multilingual Support

DeepSeek Coder is trained in both English and Chinese, making it an excellent tool for developers across different regions and working with multilingual codebases.

4. High Performance Across Benchmarks

DeepSeek Coder achieves state-of-the-art performance among publicly available code models, excelling in benchmarks such as:

• HumanEval


• MultiPL-E


• MBPP


• DS-1000


• APPS

Its efficiency and high performance make it an indispensable tool for developers seeking an AI-powered coding assistant.

5. Open-Source Accessibility

DeepSeek Coder is released under a permissive license, making it available for both research and commercial use. Developers can access the model via GitHub and integrate it into their projects as needed.

Who Can Benefit from DeepSeek Coder?

DeepSeek Coder is designed for a diverse range of users, including:

Professional Developers

Developers working on various programming languages can leverage DeepSeek Coder for:

• Code snippet generation


• Code completion assistance


• Solution recommendations

Educators and Students

DeepSeek Coder serves as an excellent learning tool by:

• Providing explanations for complex coding concepts


• Offering code examples for learning new programming languages


• Helping students and educators understand best coding practices

Researchers

With its open-source nature, DeepSeek Coder enables

• Further exploration in code generation and AI-driven programming assistance


• Advancements in AI models for software development


• Integration into experimental projects for research purposes

Use Cases for DeepSeek Coder

1. Code Generation

Developers can input specific prompts to generate functional code snippets in multiple programming languages, including Python, JavaScript, Java, C++, and more.

2. Code Completion

The model predicts and completes partial code, streamlining the coding process and reducing the effort required for repetitive tasks.

3. Code Explanation

DeepSeek Coder provides clear and concise explanations for given code, making it an excellent tool for code reviews, debugging, and learning.

4. Code Infilling

With its 16,000-token context window, DeepSeek Coder can analyze large codebases and fill in missing segments, ensuring seamless code integration.

Getting Started with DeepSeek Coder: A Sample Project

To demonstrate how DeepSeek Coder can assist in development, let's walk through a sample project where we use the model to generate a quicksort algorithm in Python.

Step 1: Access the Model

DeepSeek Coder can be accessed through platforms such as Hugging Face or via API integrations.

Step 2: Set Up the Environment

Before using DeepSeek Coder, ensure you have the necessary dependencies installed:

Step 3: Load the Model

Use the following Python code to load the DeepSeek Coder model and tokenizer:

Step 4: Generate the Quicksort Function

Define an input prompt and generate the corresponding code snippet:

The model will output an efficient implementation of the quicksort algorithm based on the provided prompt.

DeepSeek-Coder-V2: The Next-Generation Open-Source Code Intelligence Model

DeepSeek-Coder-V2 is a cutting-edge, open-source Mixture-of-Experts (MoE) code language model developed by DeepSeek AI to push the boundaries of code intelligence. Designed to provide advanced code generation, completion, and infilling, this model caters to a wide spectrum of programming languages, delivering performance on par with leading closed-source models like GPT-4 Turbo for code-related tasks.

Key Features

• Enhanced Training: DeepSeek-Coder-V2 builds upon its predecessor, DeepSeek-V2, with an additional 6 trillion tokens of training data. This extensive training further strengthens its coding, mathematical reasoning, and general language understanding capabilities.


• Expanded Language Support: The model now supports 338 programming languages, significantly improving its versatility for developers working across various coding environments.


• Extended Context Length: With an expanded context window of 128K tokens, DeepSeek-Coder-V2 efficiently handles large-scale codebases and provides more comprehensive assistance in complex programming scenarios.

Model Variants

DeepSeek-Coder-V2 is available in multiple configurations, allowing users to choose a model that aligns with their computational resources and requirements:

• DeepSeek-Coder-V2-Lite-Base: 16B total parameters (2.4B active), 128K token context window.


• DeepSeek-Coder-V2-Lite-Instruct: 16B total parameters (2.4B active), 128K token context window.


• DeepSeek-Coder-V2-Base: 236B total parameters (21B active), 128K token context window.


• DeepSeek-Coder-V2-Instruct: 236B total parameters (21B active), 128K token context window.

Performance Benchmarks

DeepSeek-Coder-V2 excels in standardized coding and math benchmarks, surpassing notable closed-source models like GPT-4 Turbo, Claude 3 Opus, and Gemini 1.5 Pro, proving its superiority in real-world coding applications.

Access & Licensing

Released under a permissive license, DeepSeek-Coder-V2 is available for research and commercial use. Developers can download and deploy the models via platforms such as Hugging Face.
For more details and access to the models, visit the official DeepSeek-Coder-V2 GitHub repository.

DeepSeek-Coder-V2 represents a significant leap in open-source AI-powered code intelligence, offering developers, educators, and researchers a powerful tool to streamline coding workflows, enhance productivity, and redefine the future of AI-assisted programming.

DeepSeek Coder VSCode: AI-Powered Coding Assistance in Visual Studio Code

DeepSeek Coder transforms Visual Studio Code into a smart AI-assisted development environment, significantly enhancing productivity with features like intelligent autocompletion, debugging, and refactoring.

By integrating DeepSeek Coder with VSCode, developers can streamline their workflows, boost efficiency, and write better code faster.

For more details, visit the official GitHub repository and start coding with DeepSeek Coder today!

DeepSeek Coder API: Seamless AI-Powered Code Assistance

The DeepSeek Coder API empowers developers by integrating advanced code generation, completion, and infilling capabilities into their applications. Designed to be fully compatible with OpenAI’s API format, it enables seamless adoption using existing OpenAI SDKs and software, allowing for a smooth transition and easy integration into development environments.

Getting Started with the DeepSeek Coder API

1. Obtain an API Key

To access DeepSeek Coder's AI-powered functionalities, follow these steps:

• Visit the DeepSeek API Documentation and apply for an API key.
• Use the API key to authenticate and interact with the DeepSeek Coder API.

2. Configure Your Environment

To set up API requests, use the following configuration:

• Base URL: https://api.deepseek.com
• Authentication: Include your API key in the authorization header for every request.

3. Making API Requests

The DeepSeek Coder API supports multiple models tailored for different AI-powered development needs, including:

• DeepSeek-chat – Optimized for conversational AI and interactive assistance (DeepSeek-V3).
• DeepSeek-reasoner – Enhanced for reasoning and structured problem-solving tasks (DeepSeek-R1).

Developers can leverage these models for real-time code completion, AI-powered debugging, and efficient code generation.

DeepSeek-Coder-V2 on HuggingFace

DeepSeek-Coder-V2 is an open-source Mixture-of-Experts (MoE) code language model developed by DeepSeek AI, designed to revolutionize AI-assisted programming. Available on Hugging Face, this model provides code generation, completion, and infilling capabilities across a vast array of programming languages, achieving performance comparable to leading closed-source models like GPT-4 Turbo in code-specific tasks.

Model Variants on Hugging Face

DeepSeek-Coder-V2 is available in multiple configurations, allowing developers to choose the best model based on computational resources and project needs:

• DeepSeek-Coder-V2-Lite-Base: 16B total parameters (2.4B active), 128K token context window.


• DeepSeek-Coder-V2-Lite-Instruct: 16B total parameters (2.4B active), optimized for instruction-based tasks.


• DeepSeek-Coder-V2-Base: 236B total parameters (21B active), advanced model for high-end AI-assisted development.


• DeepSeek-Coder-V2-Instruct: 236B total parameters (21B active), instruction-tuned for complex programming interactions.

Accessing DeepSeek-Coder-V2 on Hugging Face

The models are available on Hugging Face for easy integration into machine learning pipelines and development environments. Developers can download and fine-tune these models or deploy them using Hugging Face's Inference API.

How to Use DeepSeek-Coder-V2 from Hugging Face

Install Hugging Face Transformers and load the model: