Detoxification of large language models via regularized fine tuning
Large language models (LLMs) have demonstrated impressive benefits across different tasks, but as it has been clear in several cases, they have the risk of producing inappropriate, unsafe or partial output. When generating resorts, a successful trained LLM must comply with a set of policies specified by its creator; For example, the developer may limit … Read more