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Introducing InstructLab - A new community-based approach to build truly open-source LLMs

By Armand Ruiz posted Wed May 08, 2024 07:46 AM

  
Open Source AI is Broken. And at IBM, we believe we have a solution. Let me explain...

Open Source in Software is great because you tap into:

- Collaborative Improvement: a collective effort, as contributors worldwide enhance projects through shared insights and diverse expertise.

- Continuous Refinement: The code constantly evolves as community contributions are merged, leading to improved features, functionality, and performance.

Collective Ownership and a sense of pride motivate individuals to contribute towards a common goal.

BUT with AI, this isn't working.

Thousands of forks appear every time a new open-source model is released, but they rarely merge into the base model, preventing meaningful community improvements.

In simple terms, the original model is not getting more intelligent.

For example, Llama 3 was released 19 days ago, and there are already over 6,000 Llama 3 models on Hugging Face! Each represents a different version, and there's no straightforward mechanism for building upon each other.

Yesterday, we launched 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗟𝗮𝗯, which we believe entirely will change the game.

InstructLab addresses these challenges by enabling contributors to add specific skills or knowledge to a model.

Its model-agnostic technology allows upstream creators to regularly update their open-source models by integrating new skills instead of fully retraining them, promoting efficient and collaborative development.

InstructLab employs the LAB technique, which uses taxonomy-guided synthetic data generation and a multi-phase tuning framework to align models, making them more accessible by reducing reliance on costly human annotations.

🤩 We are super excited about the possibilities of InstructLab, a project that fosters collaboration by leveraging diverse expertise and perspectives to improve model alignment.

Want to learn more? Here are some links you cannot miss:

- Project: https://instructlab.ai/
- Research Paper: https://lnkd.in/e3r25GuT
- News: https://lnkd.in/eVNctKV6
- Explainer: https://lnkd.in/eJ3ZqN9A

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