K2 is a cutting-edge giant language mannequin (LLM) developed by LLM360 in collaboration with MBZUAI and Petuum. This mannequin, generally known as K2-65B, boasts 65 billion parameters and is absolutely reproducible, which means all artifacts, together with code, knowledge, mannequin checkpoints, and intermediate outcomes, are open-sourced and accessible to the general public. This stage of transparency goals to demystify the coaching recipe used for comparable fashions, reminiscent of Llama 2 70B and offers a transparent perception into the event course of and efficiency metrics.
The event of K2 was a collaborative effort amongst a number of outstanding establishments: MBZUAI, Petuum, and LLM360. This collaboration leveraged the experience and assets of those organizations to create a state-of-the-art language mannequin that stands out for its efficiency and transparency. The mannequin is out there beneath the Apache 2.0 license, selling widespread use and additional growth by the group.
LLM360 has supplied a sturdy set of evaluations for K2, encompassing basic and domain-specific benchmarks. These evaluations cowl medical, mathematical, and coding data, making certain the mannequin performs effectively throughout varied duties and domains. The LLM360 Efficiency and Analysis Assortment and the K2 Weights and Biases undertaking doc an in depth evaluation of K2’s efficiency.
K2 was educated utilizing various datasets to realize outcomes corresponding to these of the Llama 2 70B mannequin. The coaching course of concerned two levels, extensively utilizing datasets reminiscent of dm-math, PubMed-abstracts, uspto, and others, totaling 1.3 trillion tokens. This complete knowledge combine ensured that K2 developed a broad understanding and functionality throughout varied topics and languages.
LLM360 has made K2’s intermediate checkpoints out there, permitting researchers and builders to trace the mannequin’s growth and enchancment over time. That is a part of K2’s absolutely reproducible nature, offering transparency and facilitating additional analysis and growth. Tutorials for reproducing the pretraining and finetuning processes are additionally supplied, catering to educational and trade researchers.
Additionally, LLM360 is an open analysis lab that allows community-owned synthetic basic intelligence (AGI) by way of open-source giant mannequin analysis and growth. They purpose to create an open ecosystem with equitable computational assets, high-quality knowledge, and a flowing technical data base to make sure moral AGI growth and common entry. LLM360 goals to empower innovators by advancing the capabilities of huge language fashions and fostering a collaborative setting for analysis and growth.
In conclusion, K2 by LLM360 presents transparency, efficiency, and a sturdy growth framework. By open-source collaboration and complete analysis, K2 units a brand new normal for LLM growth, making certain moral practices and broad accessibility for future improvements in AI.
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