goldfish-models
/

uzb_latn_100mb

@@ -20,6 +20,8 @@ Goldfish is a suite of monolingual language models trained for 350 languages.
 This model is the <b>Uzbek</b> (Latin script) model trained on 100MB of data, after accounting for an estimated byte premium of 1.23; content-matched text in Uzbek takes on average 1.23x as many UTF-8 bytes to encode as English.
 The Goldfish models are trained primarily for comparability across languages and for low-resource languages; Goldfish performance for high-resource languages is not designed to be comparable with modern large language models (LLMs).
 Note: uzb_latn is a [macrolanguage](https://iso639-3.sil.org/code_tables/639/data) code. Individual language code uzn_latn (Northern Uzbek) is included in Goldfish, although with less data.
 All training and hyperparameter details are in our paper, [Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2024)](https://github.com/tylerachang/goldfish/blob/main/goldfish_paper_20240815.pdf).

 This model is the <b>Uzbek</b> (Latin script) model trained on 100MB of data, after accounting for an estimated byte premium of 1.23; content-matched text in Uzbek takes on average 1.23x as many UTF-8 bytes to encode as English.
 The Goldfish models are trained primarily for comparability across languages and for low-resource languages; Goldfish performance for high-resource languages is not designed to be comparable with modern large language models (LLMs).
+Note: This language is available in Goldfish with other scripts (writing systems). See: uzb_cyrl.
 Note: uzb_latn is a [macrolanguage](https://iso639-3.sil.org/code_tables/639/data) code. Individual language code uzn_latn (Northern Uzbek) is included in Goldfish, although with less data.
 All training and hyperparameter details are in our paper, [Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2024)](https://github.com/tylerachang/goldfish/blob/main/goldfish_paper_20240815.pdf).