Goldfish is a suite of monolingual language models trained for 350 languages.
This model is the
Newari
(Devanagari script) model trained on 12MB of data (all our data in the language), after accounting for an estimated byte premium of 2.56; content-matched text in Newari takes on average 2.56x 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: new_deva is an
individual language
code. It is not contained in any macrolanguage codes contained in Goldfish (for script deva).
To access all Goldfish model details programmatically, see
https://github.com/tylerachang/goldfish/blob/main/model_details.json
.
All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
Details for this model specifically:
Architecture: gpt2
Parameters: 124770816
Maximum sequence length: 512 tokens
Training text data (raw): 31.86MB
Training text data (byte premium scaled): 12.445MB
Training tokens: 2927616 (x10 epochs)
Vocabulary size: 50000
Compute cost: 1.4934929965056e+16 FLOPs or ~1.4 NVIDIA A6000 GPU hours
Training datasets (percentages prior to deduplication):
@article{chang-etal-2024-goldfish,
title={Goldfish: Monolingual Language Models for 350 Languages},
author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
journal={Preprint},
year={2024},
}
Runs of goldfish-models new_deva_full on huggingface.co
31
Total runs
0
24-hour runs
0
3-day runs
3
7-day runs
19
30-day runs
More Information About new_deva_full huggingface.co Model
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goldfish-models new_deva_full online free url in huggingface.co:
new_deva_full is an open source model from GitHub that offers a free installation service, and any user can find new_deva_full on GitHub to install. At the same time, huggingface.co provides the effect of new_deva_full install, users can directly use new_deva_full installed effect in huggingface.co for debugging and trial. It also supports api for free installation.