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Maintained by the community, for the community.\n\n## Contents\n\n- [Official Resources](#official-resources)\n- [Models](#models)\n- [Technical Reports](#technical-reports)\n- [Tools and Applications](#tools-and-applications)\n- [Prompts](#prompts)\n- [Tutorials and Documentation](#tutorials-and-documentation)\n- [Community Projects](#community-projects)\n- [Other Awesome Lists](#other-awesome-lists)\n- [How to Contribute](#how-to-contribute)\n- [License](#license)\n- [Acknowledgments](#acknowledgments)\n\n---\n\n## Official Resources\n\n- [🌐 DeepSeek Website](https://deepseek.com/) - Official portal for product updates and research\n- [💻 DeepSeek GitHub](https://github.com/deepseek-ai) - Official code repositories\n- [🤖 DeepSeek Chat](https://chat.deepseek.com/) - Live demo of conversational AI\n- [📱 DeepSeek App](https://download.deepseek.com/app/) - Mobile application for iOS and Android\n- [📄 API Documentation](https://api-docs.deepseek.com/) - Official API reference\n- [💰 API Pricing](https://api-docs.deepseek.com/quick_start/pricing) - Detailed pricing information for API usage\n- [📊 Service Status](https://status.deepseek.com/) - Real-time service status monitoring\n\n---\n\n## Models\n\n### Foundation Models\n- [🧠 DeepSeek-LLM](https://github.com/deepseek-ai/DeepSeek-LLM) - 7B/67B parameter general-purpose LLM\n- [🚀 DeepSeek-V2](https://github.com/deepseek-ai/DeepSeek-V2) - MoE model with 236B total params (21B activated), 128k context\n- [⚡ DeepSeek-V3](https://github.com/deepseek-ai/DeepSeek-V3) - MoE model with 671B total params (37B activated), 128k context\n- [🔬 DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) - RL-enhanced model with 60.9% on MATH, 128k context\n\n### Code Models\n- [💻 DeepSeek-Coder: Let the Code Write Itself](https://arxiv.org/abs/2401.14196) - Introduces the first version of DeepSeek Coder model\n- [🔧 DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence](https://arxiv.org/abs/2406.11931) - Presents an open-source MoE code language model\n- [🛠️ DeepSeek-MoE](https://github.com/deepseek-ai/DeepSeek-MoE) - Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models\n\n### Multimodal Models\n- [🖼️ DeepSeek-VL](https://github.com/deepseek-ai/DeepSeek-VL) - Vision-language model for real-world understanding (1.3B/7B), 4096 context length\n- [🎨 Janus](https://github.com/deepseek-ai/Janus) - Unified Multimodal Understanding and Generation Models\n- [🌌 DreamCraft3D](https://github.com/deepseek-ai/DreamCraft3D) - Official Implementation of DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior\n\n### Math Models\n- [🧮 DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://arxiv.org/abs/2402.03300) - Introduces a 7B math specialist model achieving 51.7% on MATH benchmark\n\n### Fine-tuning \u0026 Optimization\n- [⚙️ ESFT](https://github.com/deepseek-ai/ESFT) - Expert Specialized Fine-Tuning\n\n### Integration \u0026 Tools\n- [🔗 awesome-deepseek-integration](https://github.com/deepseek-ai/awesome-deepseek-integration) - A curated list of DeepSeek integration resources\n- [🛠️ awesome-deepseek-coder](https://github.com/deepseek-ai/awesome-deepseek-coder) - A curated list of open-source projects related to DeepSeek Coder\n\n---\n\n## Technical Reports\n\n### Foundation Models\n- [📜 DeepSeek LLM: Scaling Open-Source Language Models with Longtermism](https://arxiv.org/abs/2401.02954) - Introduces the training methodology and innovations of DeepSeek base models\n- [🚀 DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model](https://arxiv.org/abs/2405.04434) - Presents the architecture and training strategies of DeepSeek-V2\n- [⚡ DeepSeek-V3 Technical Report](https://arxiv.org/abs/2412.19437) - Details the MoE architecture with 671B total parameters\n- [🔬 DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://arxiv.org/abs/2501.12948) - Introduces reinforcement learning approach for reasoning capabilities\n\n### Code Models\n- [💻 DeepSeek-Coder: When the Large Language Model Meets Programming](https://arxiv.org/abs/2401.14196) - In-depth exploration of DeepSeek Coder's technical details and performance\n- [🔧 DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence](https://arxiv.org/abs/2406.11931) - Presents an open-source MoE code language model\n\n### Math Models\n- [🧮 DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://arxiv.org/abs/2402.03300) - Introduces a 7B math specialist model achieving 51.7% on MATH benchmark\n\n### Usage Guides\n- [📚 DeepSeek Prompt Library](https://api-docs.deepseek.com/prompt-library) - Collection of curated prompts and examples\n\n---\n\n## Tools and Applications\n\n### Development Tools\n- [⚡ API Quickstart](https://api-docs.deepseek.com/) - Get started in 5 minutes\n\n### Integrations\n- [🤗 Hugging Face Models](https://huggingface.co/deepseek-ai) - Model hub integration\n\n### Playgrounds\n- [🧪 Colab Notebooks](https://colab.research.google.com/github/deepseek-ai) - Free experimentation\n\n---\n\n## Prompts\n\n- [📚 Official Prompt Library](https://api-docs.deepseek.com/prompt-library) - Curated collection of prompts and examples\n\n---\n\n## Tutorials and Documentation\n\n- [🚀 Quickstart Guide](https://api-docs.deepseek.com/) - First steps with DeepSeek\n- [📚 Full Documentation](https://api-docs.deepseek.com/) - Comprehensive technical reference\n\n---\n\n## Community Projects\n\n### Open Source\n- [🤗 Hugging Face Models](https://huggingface.co/deepseek-ai) - Model documentation and demos\n\n---\n\n## Other Awesome Lists\n\n- [🌟 Awesome LLM](https://github.com/Hannibal046/Awesome-LLM) - Large Language Models resources\n- [🔓 Awesome Open LLM](https://github.com/eugeneyan/open-llms) - Open-source LLMs\n- [🌟 Awesome-Chinese-LLM](https://github.com/HqWu-HITCS/Awesome-Chinese-LLM) - A curated list of Chinese LLMs, focusing on small-scale, privately deployable models with low training costs\n- [🛡️ Awesome LLM Security](https://github.com/corca-ai/awesome-llm-security) - Security best practices\n\n---\n\n## How to Contribute\n\nYour contributions are welcome! Please:\n1. Read our [Contribution Guidelines](CONTRIBUTING.md)\n2. Ensure links are relevant and functional\n3. Add concise descriptions (50-150 characters)\n4. Follow the [Code of Conduct](CODE_OF_CONDUCT.md)\n\n---\n\n## License\n\n[![CC BY 4.0](https://licensebuttons.net/l/by/4.0/88x31.png)](https://creativecommons.org/licenses/by/4.0/)\n\n---\n\n## Acknowledgments\n\nSpecial thanks to:\n- DeepSeek engineering team for open-source contributions\n- [@realShineHuang](https://github.com/realShineHuang) for maintaining this list\n- All [contributors](CONTRIBUTORS.md) (view full list)","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/leonxcom%2Fawesome-deepseek/projects"}