goldfish-models commited on
Commit
47cc633
1 Parent(s): dcc3fc4

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +63 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ ---
3
+ license: apache-2.0
4
+ language:
5
+ - kmr
6
+ - kur
7
+ datasets:
8
+ - allenai/nllb
9
+ - cis-lmu/Glot500
10
+ - sil-ai/bloom-lm
11
+ library_name: transformers
12
+ pipeline_tag: text-generation
13
+ tags:
14
+ - goldfish
15
+
16
+ ---
17
+
18
+ # kmr_latn_5mb
19
+
20
+ Goldfish is a suite of monolingual language models trained for 350 languages.
21
+ This model is the <b>Northern Kurdish</b> (Latin script) model trained on 5MB of data, after accounting for an estimated byte premium of 1.03; content-matched text in Northern Kurdish takes on average 1.03x as many UTF-8 bytes to encode as English.
22
+ 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).
23
+
24
+ Note: kmr_latn is an [individual language](https://iso639-3.sil.org/code_tables/639/data) code. Macrolanguage code kur_latn (Kurdish) is included in Goldfish. Consider using that model depending on your use case.
25
+
26
+ 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).
27
+
28
+ Training code and sample usage: https://github.com/tylerachang/goldfish
29
+
30
+ Sample usage also in this Google Colab: [link](https://colab.research.google.com/drive/1rHFpnQsyXJ32ONwCosWZ7frjOYjbGCXG?usp=sharing)
31
+
32
+ ## Model details:
33
+
34
+ To access all Goldfish model details programmatically, see https://github.com/tylerachang/goldfish/model_details.json.
35
+ All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
36
+ Details for this model specifically:
37
+
38
+ * Architecture: gpt2
39
+ * Parameters: 39087104
40
+ * Maximum sequence length: 512 tokens
41
+ * Training text data (raw): 5.17MB
42
+ * Training text data (byte premium scaled): 5.005MB
43
+ * Training tokens: 1204736 (x10 epochs)
44
+ * Vocabulary size: 50000
45
+ * Compute cost: 910420287160320.0 FLOPs or ~0.1 NVIDIA A6000 GPU hours
46
+
47
+ Training datasets (percentages prior to deduplication):
48
+ * 98.85869%: [NLLB (CommonCrawl and ParaCrawl)](https://huggingface.co/datasets/allenai/nllb)
49
+ * 1.14131%: [Glot500](https://huggingface.co/datasets/cis-lmu/Glot500), including [BLOOM](https://huggingface.co/datasets/sil-ai/bloom-lm), [TICO](https://tico-19.github.io/)
50
+
51
+
52
+ ## Citation
53
+
54
+ If you use this model, please cite:
55
+
56
+ ```
57
+ @article{chang-etal-2024-goldfish,
58
+ title={Goldfish: Monolingual Language Models for 350 Languages},
59
+ author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
60
+ journal={Preprint},
61
+ year={2024},
62
+ }
63
+ ```