# deepseek-ai/deepseek-llm

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7,100 stars · 1,100 forks · Makefile · MIT

## Links

- GitHub: https://github.com/deepseek-ai/deepseek-LLM
- Homepage: https://chat.deepseek.com/
- awesome-repositories: https://awesome-repositories.com/repository/deepseek-ai-deepseek-llm.md

## Description

DeepSeek-LLM is a large language model and causal language model designed for natural language generation. It functions as a multi-lingual system capable of predicting the next token in a sequence to perform text completion and conversational generation.

The model is specialized for logical reasoning, specifically as a code and math LLM. This enables it to perform complex problem solving, which includes generating executable code and solving mathematical equations through step-by-step analysis.

The system's broader capabilities cover conversational AI, including the generation of chat completions and text sequences across multiple languages. Its functional surface extends to automated code generation and the production of coherent text for various writing tasks.

## Tags

### Artificial Intelligence & ML

- [Causal Language Modeling](https://awesome-repositories.com/f/artificial-intelligence-ml/text-generation-strategies/token-prediction/causal-language-modeling.md) — Functions as a causal language model that predicts the next token for text completion and conversation.
- [Complex Problem Solving](https://awesome-repositories.com/f/artificial-intelligence-ml/complex-problem-solving.md) — Applies advanced reasoning and step-by-step analysis to solve complex mathematical equations.
- [Conversational AI](https://awesome-repositories.com/f/artificial-intelligence-ml/conversational-ai.md) — Provides a system for interactive, context-aware dialogue generation across multiple languages.
- [Large Language Models](https://awesome-repositories.com/f/artificial-intelligence-ml/large-language-models.md) — Operates as a large language model trained on massive datasets for complex reasoning and generation.
- [Sparse Routing Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-training-and-tuning/fine-tuning-and-customization/model-customization/mixture-of-experts/sparse-routing-architectures.md) — Employs a mixture-of-experts architecture to scale parameter count without increasing computational cost.
- [Causal Masking](https://awesome-repositories.com/f/artificial-intelligence-ml/masked-language-modeling/causal-masking.md) — Implements unidirectional causal masking to enable autoregressive text generation during training.
- [Grouped-Query Attention](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-head-attention-mechanisms/grouped-query-attention.md) — Utilizes grouped-query attention to reduce memory bandwidth requirements for large batch inference.
- [Latent Attention Mechanisms](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-head-attention-mechanisms/latent-attention-mechanisms.md) — Compresses key-value caches into latent vectors to optimize memory usage and throughput during inference.
- [Multilingual Language Models](https://awesome-repositories.com/f/artificial-intelligence-ml/multilingual-language-models.md) — Supports text processing and generation across multiple different languages and scripts.
- [Natural Language Code Generators](https://awesome-repositories.com/f/artificial-intelligence-ml/natural-language-code-generators.md) — Translates natural language descriptions into executable source code to solve technical programming challenges.
- [Natural Language Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/natural-language-generation.md) — Produces coherent and contextually relevant natural language text for diverse writing tasks.
- [RMSNorm Layers](https://awesome-repositories.com/f/artificial-intelligence-ml/normalization-layers/rmsnorm-layers.md) — Uses root mean square layer normalization to stabilize training and accelerate convergence.
- [Rotary Positional Embeddings](https://awesome-repositories.com/f/artificial-intelligence-ml/positional-embedding-techniques/rotary-positional-embeddings.md) — Applies rotary positional embeddings to maintain long-context coherence through relative token positioning.
- [Chat Completion Services](https://awesome-repositories.com/f/artificial-intelligence-ml/chat-completion-services.md) — Generates human-like dialogue through structured conversational turn sequences. ([source](https://github.com/deepseek-ai/deepseek-llm#readme))
- [Text Sequence Generation](https://awesome-repositories.com/f/artificial-intelligence-ml/sequence-generation/autoregressive-text-generation/text-sequence-generation.md) — Predicts subsequent tokens in a text stream to perform natural language completion. ([source](https://github.com/deepseek-ai/deepseek-llm#readme))

### Part of an Awesome List

- [Reasoning And Math Models](https://awesome-repositories.com/f/awesome-lists/ai/reasoning-and-math-models.md) — Specializes in logical reasoning for mathematical problem solving and executable code production.
- [General Purpose Models](https://awesome-repositories.com/f/awesome-lists/ai/general-purpose-models.md) — High-performance base and chat models for diverse language tasks.