LLM y modelos fundacionales

DeepSeek-R1 — Reasoning model research and evaluation

deepseek-ai/DeepSeek-R1

An open-source project focused on reasoning model research and evaluation.

Abrir repositorio oficial ↗
★ 92KEstrellas
⑂ 11,7KBifurcaciones
36Problemas abiertos
PythonIdioma
MITLicencia
Q@project.QualityScorePuntuación editorial

Capturas de pantalla del proyecto

Captura de pantalla de DeepSeek-R1 — Reasoning model research and evaluation Captura de pantalla de DeepSeek-R1 — Reasoning model research and evaluation

Resumen

deepseek-ai/DeepSeek-R1 is an open-source project in ToolAI's LLM and foundation models category. An open-source project focused on reasoning model research and evaluation. 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.

Características principales

  • Official repository maintained by deepseek-ai; the repository description identifies it as reasoning model research and evaluation.
  • 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.

Requisitos, instalación y guía rápida

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-R1
cd DeepSeek-R1

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.

Uso

This page is an objective orientation for reasoning model research and evaluation. 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.

Compatibilidad de modelos y casos de uso

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.

Notas sobre la licencia y los riesgos

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.

Lanzamiento y mantenimiento

Snapshot: 91,981 stars, 11,706 forks and 39 open issues; repository creation is not stated and last pushed date is 2025-06-27 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.

ClearML

clearml/clearml

★ 6,8KPython