Improving LLM -Fores with Better Data Organization
The documents used to train a large language model (LLM) are typically linked to forming a single “super document”, which is then divided into sequences, as the model’s context length. This improves exercise efficiency, but often results in unnecessary trunkings where individual documents are divided across successive sequences. Related content Coherent parameter handling and prior … Read more