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Found 2 papers, 1 papers with code
Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages
By simply adding the chat vector to a continual pre-trained model's weights, we can endow the model with chat capabilities in new languages without the need for further training.
Compressing Transformer-based self-supervised models for speech processing
Despite the success of Transformers in self- supervised learning with applications to various downstream tasks, the computational cost of training and inference remains a major challenge for applying these models to a wide spectrum of devices.
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