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Words don’t come easy (… to LLMs): Universal Text-Encoding for dynamic, multi-lingual alphabets revolutionizing efficiency and effectiveness for LLM training and inference

The remarkable advancements of Large Language Models (LLMs) frequently capture attention as they become valuable collaborators in daily situations, all while progressing towards breakthroughs beyond simple language completion.
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Introducing Pharia-1-LLM: transparent and compliant

We are pleased to announce our new foundation model family that includes Pharia-1-LLM-7B-control and Pharia-1-LLM-7B-control-aligned, now publicly available under the Open Aleph License, which explicitly allows for non-commercial research and educational use.
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Quality Diversity through AI Feedback

Language models carry implicit distributional biases based on their training data, which can reinforce existing norms. In this work, we take one step towards addressing the challenge of unwanted biases by enabling language models to return outputs with a broader spectrum of attribute traits, specified by a user. This is achieved by asking language models to evaluate and modify their outputs.
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