Goldfish is a suite of monolingual language models trained for 350 languages.
This model is the
Dhivehi
(Thaana script) model trained on 10MB of data, after accounting for an estimated byte premium of 2.00; content-matched text in Dhivehi takes on average 2.00x 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: div_thaa is an
individual language
code. It is not contained in any macrolanguage codes contained in Goldfish (for script thaa).
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: 39087104
Maximum sequence length: 512 tokens
Training text data (raw): 19.98MB
Training text data (byte premium scaled): 10.005MB
Training tokens: 1890304 (x10 epochs)
Vocabulary size: 50000
Compute cost: 1428872893562880.0 FLOPs or ~0.1 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 div_thaa_10mb on huggingface.co
34
Total runs
0
24-hour runs
-2
3-day runs
3
7-day runs
4
30-day runs
More Information About div_thaa_10mb huggingface.co Model
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goldfish-models div_thaa_10mb online free url in huggingface.co:
div_thaa_10mb is an open source model from GitHub that offers a free installation service, and any user can find div_thaa_10mb on GitHub to install. At the same time, huggingface.co provides the effect of div_thaa_10mb install, users can directly use div_thaa_10mb installed effect in huggingface.co for debugging and trial. It also supports api for free installation.