gft generalizes the examples so users can do much of that in a single line of gft code (with comparable performance). gft supports most of the arguments in the examples on the hubs, so it is possible to tune hyper-parameters such as batch size, learning rate, and stopping rules.
May 23, 2022 · This paper proposed gft, a little language for fine-tuning pretrained base (foundation) models. Little languages make it easier for a broader ...
May 23, 2022 · Abstract. This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022.
This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022 tutorial. gft makes deep nets accessible to a ...
gft contains 4 main functions: gft_fit: fit a pretrained model to data (aka fine-tuning); gft_predict: apply a model to inputs (aka inference) ...
This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022 tutorial. gft makes deep nets accessible to a broad ...
Emerging trends: General fine-tuning (gft). Authors: K. Church, X. Cai, Y. Ying, Z. Chen, G. Xun, Y. Bian. (2022). Emerging tren [...] Emerging trends: SOTA- ...
Jun 11, 2024 · Many contemporary models are multi-modal, capable of simultaneously working with multiple languages, text and multimedia, encoding and decoding.
This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022 tutorial. gft makes deep nets accessible to a broad ...
Aug 23, 2024 · This technical report thoroughly examines the process of fine-tuning Large Language Models (LLMs), integrating theoretical insights and practical applications.