goldfish-models
/

rus_cyrl_1000mb

@@ -18,6 +18,8 @@ Goldfish is a suite of monolingual language models trained for 350 languages.
 This model is the <b>Russian</b> (Cyrillic script) model trained on 1000MB of data, after accounting for an estimated byte premium of 1.82; content-matched text in Russian takes on average 1.82x 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: rus_cyrl is an [individual language](https://iso639-3.sil.org/code_tables/639/data) code. It is not contained in any macrolanguage codes contained in Goldfish (for script cyrl).
 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>Russian</b> (Cyrillic script) model trained on 1000MB of data, after accounting for an estimated byte premium of 1.82; content-matched text in Russian takes on average 1.82x 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: rus_latn.
 Note: rus_cyrl is an [individual language](https://iso639-3.sil.org/code_tables/639/data) code. It is not contained in any macrolanguage codes contained in Goldfish (for script cyrl).
 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).