Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -13,7 +13,7 @@ library_name: transformers
|
|
| 13 |
pipeline_tag: text-generation
|
| 14 |
tags:
|
| 15 |
- goldfish
|
| 16 |
-
|
| 17 |
---
|
| 18 |
|
| 19 |
# nya_latn_full
|
|
@@ -24,7 +24,7 @@ The Goldfish models are trained primarily for comparability across languages and
|
|
| 24 |
|
| 25 |
Note: nya_latn 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 latn).
|
| 26 |
|
| 27 |
-
All training and hyperparameter details are in our paper, [Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2024)](https://
|
| 28 |
|
| 29 |
Training code and sample usage: https://github.com/tylerachang/goldfish
|
| 30 |
|
|
@@ -34,6 +34,7 @@ Sample usage also in this Google Colab: [link](https://colab.research.google.com
|
|
| 34 |
|
| 35 |
To access all Goldfish model details programmatically, see https://github.com/tylerachang/goldfish/blob/main/model_details.json.
|
| 36 |
All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
|
|
|
|
| 37 |
Details for this model specifically:
|
| 38 |
|
| 39 |
* Architecture: gpt2
|
|
@@ -63,5 +64,6 @@ If you use this model, please cite:
|
|
| 63 |
author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
|
| 64 |
journal={Preprint},
|
| 65 |
year={2024},
|
|
|
|
| 66 |
}
|
| 67 |
```
|
|
|
|
| 13 |
pipeline_tag: text-generation
|
| 14 |
tags:
|
| 15 |
- goldfish
|
| 16 |
+
- arxiv:2408.10441
|
| 17 |
---
|
| 18 |
|
| 19 |
# nya_latn_full
|
|
|
|
| 24 |
|
| 25 |
Note: nya_latn 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 latn).
|
| 26 |
|
| 27 |
+
All training and hyperparameter details are in our paper, [Goldfish: Monolingual Language Models for 350 Languages (Chang et al., 2024)](https://www.arxiv.org/abs/2408.10441).
|
| 28 |
|
| 29 |
Training code and sample usage: https://github.com/tylerachang/goldfish
|
| 30 |
|
|
|
|
| 34 |
|
| 35 |
To access all Goldfish model details programmatically, see https://github.com/tylerachang/goldfish/blob/main/model_details.json.
|
| 36 |
All models are trained with a [CLS] (same as [BOS]) token prepended, and a [SEP] (same as [EOS]) token separating sequences.
|
| 37 |
+
For best results, make sure that [CLS] is prepended to your input sequence (see sample usage linked above)!
|
| 38 |
Details for this model specifically:
|
| 39 |
|
| 40 |
* Architecture: gpt2
|
|
|
|
| 64 |
author={Chang, Tyler A. and Arnett, Catherine and Tu, Zhuowen and Bergen, Benjamin K.},
|
| 65 |
journal={Preprint},
|
| 66 |
year={2024},
|
| 67 |
+
url={https://www.arxiv.org/abs/2408.10441},
|
| 68 |
}
|
| 69 |
```
|