LLM & Basismodelle

DeepSeek-V3 — Large language model research and inference

deepseek-ai/DeepSeek-V3

An open-source project focused on large language model research and inference.

Offizielles Repository öffnen ↗
★ 104,3KSterne
⑂ 16,7KForks
207Offene Issues
PythonSprache
MITLizenz
Q@project.QualityScoreRedaktionelle Bewertung

Projekt-Screenshots

Screenshot von DeepSeek-V3 — Large language model research and inference Screenshot von DeepSeek-V3 — Large language model research and inference

Übersicht

deepseek-ai/DeepSeek-V3 is an open-source project in ToolAI's LLM and foundation models category. An open-source project focused on large language model research and inference. The page is intended to help technical readers decide whether the project is worth a closer review; it is not an endorsement. The Python implementation and the repository owner deepseek-ai are recorded from the catalog metadata.

Wichtige Funktionen

  • Official repository maintained by deepseek-ai; the repository description identifies it as large language model research and inference.
  • Primary language recorded for this editorial entry: Python.
  • Repository statistics and links are shown as a dated metadata snapshot, so readers can re-check them before adoption.
  • The official README, releases and issue tracker remain the source of truth for installation and compatibility details.

Voraussetzungen, Installation und Schnellstart

Requirements depend on the current official documentation. Start with the repository's README and pin a reviewed release before production use.

git clone https://github.com/deepseek-ai/DeepSeek-V3
cd DeepSeek-V3

Use the project's documented environment manager, model weights and optional accelerators. Do not copy commands from an unverified mirror; check the release notes and lock compatible dependencies first.

Nutzung

This page is an objective orientation for large language model research and inference. Read the official quick-start example, run it in an isolated environment, and record the exact commit or release used. For an agent or model workflow, keep tool permissions narrow, validate external inputs, and measure latency and quality on a representative test set. The repository's README and examples should be consulted for API details that may change.

Modellkompatibilität und Anwendungsfälle

The repository metadata describes the project scope but does not guarantee compatibility with every model, provider, checkpoint or accelerator. Confirm supported model identifiers, tokenizer versions, hardware requirements and license terms in the official documentation before connecting it to an LLM, agent, MCP server or RAG pipeline.

Lizenz- und Risikohinweise

GitHub metadata reports the repository license as MIT. Review the repository LICENSE and any separate model, dataset, weight or third-party dependency terms before redistribution or commercial use. A missing or NOASSERTION license is not a grant of permission.

Editorial verification 2026-08-02: official repository URL, owner, description, license field and repository statistics were reviewed. License metadata: MIT. Re-check README, releases and dependency/model terms before production use.

Veröffentlichung und Wartung

Snapshot: 104,009 stars, 16,703 forks and 257 open issues; repository creation is not stated and last pushed date is 2025-08-28 when supplied by the catalog. Check the official releases page for the current version rather than treating these numbers as a guarantee of maintenance or quality.

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