Chinchilla is a family of large language models (LLMs) developed by the research team at Google DeepMind, presented in March 2022.
It considerably simplifies downstream utilization because it requires much less computer power for inference and fine-tuning.
Similar to Gopher in terms of cost, Chinchilla has 70B parameters and four times as much data.
[3] Chinchilla has an average accuracy of 67.5% on the Measuring Massive Multitask Language Understanding (MMLU) benchmark, which is 7% higher than Gopher's performance.
[4] Chinchilla contributes to developing an effective training paradigm for large autoregressive language models with limited compute resources.