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deepseek-ai/DeepSeek-Coder-V2

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6,462 نجوم·1,043 تفرعات·mit·7 مشاهدات

DeepSeek Coder V2

Features

  • Code-Focused - An open-weight model fine-tuned for code generation, completion, and reasoning across hundreds of programming languages.
  • OpenAI-Compatible APIs - Exposes the model behind a REST endpoint using the OpenAI-compatible API format.
  • Batch Inference Engines - Processes multiple code generation prompts efficiently using the vLLM inference engine for high throughput.
  • Fill-in-the-Middle Training Objectives - Trains the model to predict masked code segments from bidirectional context for insertion-based generation.
  • Generative Code Models - Generates code responses from chat messages using a large language model.
  • Code-Optimized - Processes input sequences up to 128,000 tokens, enabling reasoning over entire codebases in a single pass.
  • Long Context Processing - Handles input sequences up to 128,000 tokens for reasoning over entire codebases in a single pass.
  • HuggingFace Transformers Loaders - Loads the model through the standard Transformers library for chat, completion, and insertion modes.
  • 128K-Token Context Windows - Processes sequences of up to 128,000 tokens using rotary position embeddings and memory-efficient attention.
  • Natural Language Code Generators - Generates executable source code in hundreds of programming languages from plain-language descriptions.
  • HuggingFace Transformers Loaders - Loads the model through the standard Transformers library for inference.
  • Mixture of Experts - Uses a mixture-of-experts transformer architecture for efficient inference.
  • Code Completion - Generates context-aware code continuations and fills in missing blocks within existing files or repositories.
  • OpenAI-Compatible Servers - Exposes the model behind a REST endpoint that accepts the same request format as OpenAI's API for easy integration.
  • Bug Fixing with Explanations - Identifies errors in code and produces corrected versions alongside a description of the fix.
  • Technical - Answers questions about programming concepts, APIs, algorithms, and best practices with clear explanations.
  • Mathematical Problem Solving Toolkits - Performs multi-step mathematical reasoning to answer arithmetic, algebraic, and competition-level math questions.
  • AI-Powered Code Fixes - Identifies and repairs defects in source code by analyzing buggy snippets and producing corrected versions.
  • Code Generation Models - Advanced mixture-of-experts models for high-quality code intelligence.
  • Domain Specific Models - High-performance model specifically tuned for programming tasks.

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الأسئلة الشائعة

ما هي الميزات الرئيسية لـ deepseek-ai/deepseek-coder-v2؟

الميزات الرئيسية لـ deepseek-ai/deepseek-coder-v2 هي: Code-Focused, OpenAI-Compatible APIs, Batch Inference Engines, Fill-in-the-Middle Training Objectives, Generative Code Models, Code-Optimized, Long Context Processing, HuggingFace Transformers Loaders.

ما هي البدائل مفتوحة المصدر لـ deepseek-ai/deepseek-coder-v2؟

تشمل البدائل مفتوحة المصدر لـ deepseek-ai/deepseek-coder-v2: qwenlm/qwen2.5-coder — Qwen2.5-Coder is a code-centric large language model designed to generate, complete, and analyze source code. It… openbmb/minicpm — MiniCPM is a collection of small language models designed for local, on-device deployment in resource-constrained… nlpxucan/wizardlm — WizardLM is a large language model and instruction-tuning framework designed to execute sophisticated coding,… zai-org/glm-4 — GLM-4 is a large language model and fine-tuning framework designed for human-like text production, complex reasoning,… qwenlm/codeqwen1.5 — CodeQwen1.5 is a large language model designed for generating, completing, and analyzing code. It functions as an AI… zai-org/glm-4.5 — GLM-4.5 is a multimodal large language model and advanced reasoning system. It functions as an AI coding assistant, an…

بدائل مفتوحة المصدر لـ DeepSeek Coder V2

مشاريع مفتوحة المصدر مشابهة، مرتبة حسب عدد الميزات المشتركة مع DeepSeek Coder V2.
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    Qwen2.5-Coder is a code-centric large language model designed to generate, complete, and analyze source code. It serves as a polyglot programming model capable of producing functional code across hundreds of different programming languages. The model is optimized for reasoning over extensive software repositories, utilizing a context window that supports up to one million tokens. It also functions as an agentic coding framework, executing multi-step workflows and browser tasks through specialized function call formats. Its capabilities include large-scale codebase analysis, intelligent parti

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    MiniCPM is a collection of small language models designed for local, on-device deployment in resource-constrained environments. The project focuses on running dense Transformer models on consumer hardware, including GPUs, CPUs, and Apple Silicon, without requiring custom code forks. The project distinguishes itself through heavy optimization for edge hardware, utilizing quantized weight compression in GGUF and MLX formats to reduce memory overhead. It implements advanced inference techniques such as speculative sampling and radix-tree prefix caching to accelerate generation speed and throughp

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    WizardLM is a large language model and instruction-tuning framework designed to execute sophisticated coding, mathematical, and conversational tasks. It functions as an AI system for mathematical reasoning and code generation, as well as a synthetic dataset generator used to train other language models. The project is distinguished by its evolutionary instruction tuning, which uses a method to rewrite simple instructions into complex tasks. This process expands training dataset difficulty and produces a high volume of open-domain tasks across various difficulty levels. The system covers capa

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  • zai-org/glm-4الصورة الرمزية لـ zai-org

    zai-org/GLM-4

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    GLM-4 is a large language model and fine-tuning framework designed for human-like text production, complex reasoning, and multilingual conversation. It functions as a multimodal system capable of processing high-resolution visual content and as a long-context model designed to analyze documents with a context window of up to one million tokens. The project differentiates itself through a function calling interface that enables AI agent development by connecting the model to external APIs and real-time web browsing. It includes specialized capabilities for generating functional programming cod

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