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Found 7 papers, 0 papers with code
Aya Vision: Advancing the Frontier of Multilingual Multimodality
Building multimodal language models is fundamentally challenging: it requires aligning vision and language modalities, curating high-quality instruction data, and avoiding the degradation of existing text-only capabilities once vision is introduced.
Command A: An Enterprise-Ready Large Language Model
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases.
Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier
We introduce the Aya Expanse model family, a new generation of 8B and 32B parameter multilingual language models, aiming to address the critical challenge of developing highly performant multilingual models that match or surpass the capabilities of monolingual models.
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal value of generative AI tools in many communities.
To Code, or Not To Code? Exploring Impact of Code in Pre-training
In this work, we systematically investigate the impact of code data on general performance.
Aya 23: Open Weight Releases to Further Multilingual Progress
This technical report introduces Aya 23, a family of multilingual language models.
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model
Recent breakthroughs in large language models (LLMs) have centered around a handful of data-rich languages.
