How can language model skills be shared between participants in a federated learning infastructure? Can the trained language models learn from each other?ChatGPT-answer:
In a federated learning infrastructure, language model skills can be shared among participants through model aggregation or model averaging techniques. These techniques involve combining the trained models of multiple participants into a single model that incorporates the strengths of each individual model.
In addition, it is possible for the trained language models to learn from each other through a process called model distillation. This involves using a larger, more complex model to train a smaller, simpler model, effectively transferring the knowledge from the larger model to the smaller one. This process can help improve the performance of the smaller models and facilitate knowledge sharing between participants.
However, it's important to note that the specific techniques used for sharing language model skills in a federated learning infrastructure may vary depending on the particular use case and requirements of the participants involved.
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