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AstraMindAI

README.md

AstraMindAI

Welcome to AstraMindAI, an independent research lab dedicated to the advancement of open-source Large Language Models (LLMs) and cutting-edge Artificial Intelligence (AI). Our aim is to spearhead innovations that not only push the boundaries of what AI can achieve but also make it accessible to a broader audience.

About Us

AstraMindAI stands as a beacon of progress in the ever-evolving landscape of AI. We are a collective of thinkers, innovators, and dreamers who are dedicated to bringing the next wave of AI solutions into the open. Our work revolves around enhancing, developing, and deploying open-source LLMs that can serve a multitude of purposes across various sectors.

Our Mission

Our mission is unwavering: to democratize the transformative power of Large Language Models. By developing open-source frameworks and tools, we aim to make the advancements in LLMs freely available, enabling innovation and fostering an inclusive environment where anyone can contribute to the growth of intelligent systems.

Our Current Interest

  • Open-Source LLM Development: We are active contributors to the open-source AI ecosystem, providing robust, community-driven LLMs that serve as the backbone for a new era of intelligent applications.

Join Our Community

At AstraMindAI, we are building more than technology; we are nurturing a community. We invite you to join us on this thrilling journey to reshape the landscape of AI. Whether you're a seasoned developer, an avid researcher, or simply an enthusiast excited about AI's potential, AstraMindAI is your lab. Together, let's unlock the future of open-source intelligence.

Be part of our quest to expand the horizons of AI. Connect with us, contribute to our projects, and let your ideas take flight at AstraMindAI.

Popular repositories

  1. BitMat BitMat Public

    An efficent implementation of the method proposed in "The Era of 1-bit LLMs"

    Python 153 9

  2. Mixture-of-depths Mixture-of-depths Public

    Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"

    Python 120 7

  3. LLaMA-Factory LLaMA-Factory Public

    Forked from hiyouga/LLaMA-Factory

    Unify Efficient Fine-Tuning of 100+ LLMs

    Python 1

  4. .github .github Public

  5. LLaMA-Factory-Bitmat LLaMA-Factory-Bitmat Public

    Forked from hiyouga/LLaMA-Factory

    Unify Efficient Fine-Tuning of 100+ LLMs

    Python

Repositories

Showing 5 of 5 repositories
  • BitMat Public

    An efficent implementation of the method proposed in "The Era of 1-bit LLMs"

    astramind-ai/BitMat’s past year of commit activity
    Python 153 Apache-2.0 9 1 2 Updated Jul 2, 2024
  • Mixture-of-depths Public

    Unofficial implementation for the paper "Mixture-of-Depths: Dynamically allocating compute in transformer-based language models"

    astramind-ai/Mixture-of-depths’s past year of commit activity
    Python 120 7 4 0 Updated Jun 20, 2024
  • LLaMA-Factory Public Forked from hiyouga/LLaMA-Factory

    Unify Efficient Fine-Tuning of 100+ LLMs

    astramind-ai/LLaMA-Factory’s past year of commit activity
    Python 1 Apache-2.0 4,099 0 0 Updated Apr 18, 2024
  • LLaMA-Factory-Bitmat Public Forked from hiyouga/LLaMA-Factory

    Unify Efficient Fine-Tuning of 100+ LLMs

    astramind-ai/LLaMA-Factory-Bitmat’s past year of commit activity
    Python 0 Apache-2.0 4,099 0 0 Updated Apr 3, 2024
  • .github Public
    astramind-ai/.github’s past year of commit activity
    0 0 0 0 Updated Apr 1, 2024

People

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