neuron-explorer
Qwen3.5‑4B 전용 조향형 뉴런 탐색기, 모든 MLP 뉴런을 밀어 결과를 보관·탐색
BISHENG은 차세대 기업 AI 애플리케이션을 위한 오픈소스 대형 언어 모델(LLM) 개발·운용 플랫폼이다
BISHENG是一个面向下一代企业AI应用的开源大语言模型(LLM)开发运维平台。其强大而全面的功能包括:生成式AI工作流、检索增强生成(RAG)、智能体(Agent)、统一模型管理、评估、监督微调(SFT)、数据集管理、企业级系统管理、可观测性等。
개발 도구Python · TypeScriptGitHub @dataelement온라인운영자 미확인
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BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.
저장소 README에서 가져옴
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Proudly made by Chinese,May we, like the creators of Deepseek and Black Myth: Wukong, bring more wonder and greatness to the world.
源自中国匠心,希望我们能像 [Deepseek]、[黑神话:悟空] 团队一样,给世界带来更多美好。
BISHENG is an open LLM application devops platform, focusing on enterprise scenarios. It has been used by a large number of industry leading organizations and Fortune 500 companies.
"Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate.
🚀 Task Mode: a general-purpose agent for complex, multi-step work You give it a goal and, if needed, attach files, knowledge bases, tools and skills. The agent breaks the goal into tasks, runs them step by step, and delivers a report, PPT, Excel or Word file.
📚 Knowledge Space: an enterprise knowledge base for teams
📡 Channels: external news delivered every day, and saved as knowledge in one click
🧩 Unique BISHENG Workflow
🏢 Enterprise-grade features: the controls that enterprise AI needs
🔍 High-precision document parsing: Our document parsing models are trained on a large amount of high-quality data collected over 5 years, and you can deploy them privately for free. They include high-precision models for printed text, handwriting and rare characters, table recognition, layout analysis, and seals.
Please ensure the following conditions are met before installing BISHENG:
Recommended hardware condition: 18 virtual cores, 48G. In addition to installing BISHENG, we will also install the following third-party components by default: ES, Milvus, and Onlyoffice.
Download BISHENG
git clone https://github.com/dataelement/bisheng.git
# Enter the installation directory
cd bisheng/docker
# If the system does not have the git command, you can download the BISHENG code as a zip file.
wget https://github.com/dataelement/bisheng/archive/refs/heads/main.zip
# Unzip and enter the installation directory
unzip main.zip && cd bisheng-main/docker
Start BISHENG
docker compose -f docker-compose.yml -p bisheng up -d
After the startup is complete, access http://IP:3001 in the browser. The login page will appear, proceed with user registration.
By default, the first registered user will become the system admin.
For more installation and deployment issues, refer to::Self-hosting
This repo benefits from langchain langflow unstructured and LLaMA-Factory . Thanks for their wonderful works.
Thank you to our contributors:
Welcome to join our discussion group