

Deepseek Coder V2
Overview :
DeepSeek-Coder-V2 is an open-source Mixture-of-Experts (MoE) code language model with performance comparable to GPT4-Turbo, showcasing exceptional performance in code-specific tasks. Built upon DeepSeek-Coder-V2-Base, it has undergone further pre-training using a high-quality, multi-source corpus of 6 trillion tokens. This has significantly enhanced its coding and mathematical reasoning capabilities while maintaining its performance on general language tasks. Supported programming languages have expanded from 86 to 338, and the context length has increased from 16K to 128K.
Target Users :
DeepSeek-Coder-V2 is primarily aimed at developers, programming educators, and developers of code intelligence tools. It helps improve programming efficiency and educational quality by providing high-quality code generation, completion, and correction features, while also providing powerful backend support for code intelligence tools.
Use Cases
Developers use DeepSeek-Coder-V2 to generate code for specific functionalities.
Programming education platforms integrate the model to provide automated assessment for programming assignments.
Code intelligence tools leverage DeepSeek-Coder-V2 for code completion and error detection.
Features
Supports multiple programming languages, expanding from 86 to 338.
Context length support extends from 16K to 128K.
Outperforms closed-source models in standard benchmark tests.
Offers model downloads with different parameter sizes, including 16B and 236B parameter versions.
Provides an OpenAI-compatible API platform, supporting both free tokens and pay-as-you-go.
Offers a chat interaction experience on the DeepSeek website.
Supports local operation with detailed usage examples and guides.
How to Use
Visit the DeepSeek-Coder-V2 GitHub page to learn about the model's basic information and features.
Download the appropriate model version based on your needs, such as DeepSeek-Coder-V2-Lite-Base or DeepSeek-Coder-V2-Instruct.
Read and follow the local runtime guide to set up the environment and load the model.
Use the Huggingface Transformers library or vLLM for model inference to execute code generation, completion, or other programming assistance tasks.
Access the DeepSeek website to experience the chat interaction functionality, allowing direct conversation with the model.
Register and utilize the DeepSeek platform's API services to integrate it into your own applications.
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