goldfish-models commited on
Commit
812fe0f
1 Parent(s): 4a6a78a

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +60 -0
README.md ADDED
@@ -0,0 +1,60 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
3
+ license: apache-2.0
4
+ language:
5
+ - san
6
+ datasets:
7
+ - cis-lmu/Glot500
8
+ library_name: transformers
9
+ pipeline_tag: text-generation
10
+ tags:
11
+ - goldfish
12
+
13
+ ---
14
+
15
+ # san_latn_5mb
16
+
17
+ Goldfish is a suite of monolingual language models trained for 350 languages.
18
+ This model is the <b>Sanskrit</b> (Latin script) model trained on 5MB of data, after accounting for an estimated byte premium of 0.97; content-matched text in Sanskrit takes on average 0.97x as many UTF-8 bytes to encode as English.
19
+ 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).
20
+
21
+ Note: san_latn is a [macrolanguage](https://iso639-3.sil.org/code_tables/639/data) code. None of its contained individual languages are included in Goldfish (for script latn).
22
+
23
+ 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).
24
+
25
+ Training code and sample usage: https://github.com/tylerachang/goldfish
26
+
27
+ Sample usage also in this Google Colab: [link](https://colab.research.google.com/drive/1rHFpnQsyXJ32ONwCosWZ7frjOYjbGCXG?usp=sharing)
28
+
29
+ ## Model details:
30
+
31
+ To access all Goldfish model details programmatically, see https://github.com/tylerachang/goldfish/model_details.json.
32
+ All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
33
+ Details for this model specifically:
34
+
35
+ * Architecture: gpt2
36
+ * Parameters: 39087104
37
+ * Maximum sequence length: 512 tokens
38
+ * Training text data (raw): 4.83MB
39
+ * Training text data (byte premium scaled): 5.005MB
40
+ * Training tokens: 1022464 (x10 epochs)
41
+ * Vocabulary size: 50000
42
+ * Compute cost: 772507167621120.0 FLOPs or ~0.1 NVIDIA A6000 GPU hours
43
+
44
+ Training datasets (percentages prior to deduplication):
45
+ * 98.91275%: [eBible](https://ebible.org/find/)
46
+ * 1.08725%: [Glot500](https://huggingface.co/datasets/cis-lmu/Glot500), including [CCNet](https://github.com/facebookresearch/cc_net), [Wortschatz Leipzig Data](https://wortschatz.uni-leipzig.de/en/download)
47
+
48
+
49
+ ## Citation
50
+
51
+ If you use this model, please cite:
52
+
53
+ ```
54
+ @article{chang-etal-2024-goldfish,
55
+ title={Goldfish: Monolingual Language Models for 350 Languages},
56
+ author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
57
+ journal={Preprint},
58
+ year={2024},
59
+ }
60
+ ```