DeepSeek

Products

DeepSeekIt is an AI product developed by Hangzhou DeepSeek Artificial Intelligence Basic Technology Research Company Limited (DeepSeek AI Company). It aims to provide users with efficient information search and answer services through its powerful natural language processing capabilities. As a fully open-source and commercially available large-scale language model, DeepSeek has excellent natural language processing and code generation capabilities, making it the tool of choice for many users and researchers.

Milestones

DeepSeek's history dates back to July 2023, when it was founded and headquartered in Hangzhou by China's leading quantitative private equity giant, Phantom Square Quantitative. In just over a year, DeepSeek has made significant progress, launching several compelling open source models:

1. On November 2, 2023, release DeepSeek Coder, the first open-source big model to support code generation, debugging, and data analysis tasks in multiple programming languages.
2. On November 29, 2023, DeepSeek LLM, a general-purpose large model with a parameter size of 67 billion, was launched, including base and chat versions of 7B and 67B.
3. On May 7, 2024, DeepSeek-V2, the second generation of the open source Mixed Expert (MoE) model, was released with 236 billion total parameters and the cost of inference reduced to only RMB 1 per million tokens.
4. On December 26, 2024, DeepSeek-V3 was released with 671 billion total parameters, using an innovative MoE architecture and FP8 mixed precision training at a cost of only $5.576 million for training.
5. January 20, 2025, release of next-generation inference modelsDeepSeek-R1, with performance on par with OpenAI's o1 official version, and open source.

Key Features

DeepSeek's core features include natural language query processing and code generation. With these features, users can easily talk to AI to get the information they need or generate code. Specifically:

1. natural language query processing: DeepSeek understands and processes the user's natural language queries, providing fast and accurate answers.
2. Code Generation Capabilities: The product is equipped with code generation features that help developers quickly generate code snippets and improve development efficiency.

Usage Scenarios

DeepSeek has a wide range of application areas, mainly covering software development, data analysis, natural language processing, and many other aspects:

1. software development: DeepSeek's coding services can help developers complete their code writing and debugging work more quickly, improving development efficiency and quality. For example, DeepSeek Coder model is able to understand users' coding needs more accurately and provide high-quality code generation services through deep learning and natural language processing technologies.
2. data analysis: DeepSeek's models are able to process and analyze large amounts of data, extracting valuable information and patterns for business decision-making.
3. natural language processing (NLP): DeepSeek can be used for tasks such as text categorization, sentiment analysis, and machine translation, providing strong support for a variety of application scenarios.

In addition, DeepSeek can be used in a variety of fields such as education and training, content creation, and scientific research and exploration, demonstrating its powerful versatility.

Operating Instructions

Using the DeepSeek large language modeling algorithm is relatively simple and convenient. Users can go through the following steps:

1. Go to DeepSeek official website: Accessdeepseek.com, register and log in to your account.
2. Select Function Module: Select different functional modules according to the needs, such as text generation, semantic understanding or code generation and completion.
3. Enter a query: Enter a keyword, topic, or code snippet in the appropriate input box.
4. Submit and get resultsAfter clicking the submit button, DeepSeek will reason and calculate according to the user's input and output the processing results. Users can edit, adjust or directly use the output results as needed.

In addition, DeepSeek provides rich API interfaces and documentation support, making it easy for developers to integrate it into their applications or systems.

common problems

In the process of using DeepSeek, users may encounter some common problems, such as missing dependency libraries, version incompatibility, permission issues, etc. For these problems, users can take the following measures to solve them:

1. Checking dependent libraries: Ensure that all necessary dependency libraries are installed. The required dependencies can be installed with the pip install -r requirements.txt command.
2. version compatibility: Check if the library version is compatible with the model. Compatible library version information can be obtained by looking at the model's documentation or GitHub page.
3. Competence issues: If you encounter permission problems, try elevating the privileges with the sudo command, or prefix the install command with the -user option.

DeepSeek also provides detailed official documentation and community support where users can find solutions and tips for various problems.