File size: 2,483 Bytes
45a06c5 efd71fe 45a06c5 213db81 45a06c5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
---
language:
- multilingual
- en
- fr
- es
- de
- zh
- ar
- ru
- vi
- el
- bg
- th
- tr
- hi
- ur
- sw
datasets: wikipedia
license: apache-2.0
widget:
- text: "Google generated 46 billion [MASK] in revenue."
- text: "Paris is the capital of [MASK]."
- text: "Algiers is the largest city in [MASK]."
- text: "Paris est la [MASK] de la France."
- text: "Paris est la capitale de la [MASK]."
- text: "L'élection américaine a eu [MASK] en novembre 2020."
- text: "تقع سويسرا في [MASK] أوروبا"
- text: "إسمي محمد وأسكن في [MASK]."
---
# bert-base-15lang-cased
We are sharing smaller versions of [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) that handle a custom number of languages.
Unlike [distilbert-base-multilingual-cased](https://huggingface.co./distilbert-base-multilingual-cased), our versions give exactly the same representations produced by the original model which preserves the original accuracy.
The measurements below have been computed on a [Google Cloud n1-standard-1 machine (1 vCPU, 3.75 GB)](https://cloud.google.com/compute/docs/machine-types\#n1_machine_type):
| Model | Num parameters | Size | Memory | Loading time |
| ------------------------------- | -------------- | -------- | -------- | ------------ |
| bert-base-multilingual-cased | 178 million | 714 MB | 1400 MB | 4.2 sec |
| Geotrend/bert-base-15lang-cased | 141 million | 564 MB | 1098 MB | 3.1 sec |
Handled languages: en, fr, es, de, zh, ar, ru, vi, el, bg, th, tr, hi, ur and sw.
For more information please visit our paper: [Load What You Need: Smaller Versions of Multilingual BERT](https://www.aclweb.org/anthology/2020.sustainlp-1.16.pdf).
## How to use
```python
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Geotrend/bert-base-15lang-cased")
model = AutoModel.from_pretrained("Geotrend/bert-base-15lang-cased")
```
To generate other smaller versions of multilingual transformers please visit [our Github repo](https://github.com/Geotrend-research/smaller-transformers).
### How to cite
```bibtex
@inproceedings{smallermbert,
title={Load What You Need: Smaller Versions of Multilingual BERT},
author={Abdaoui, Amine and Pradel, Camille and Sigel, Grégoire},
booktitle={SustaiNLP / EMNLP},
year={2020}
}
```
## Contact
Please contact [email protected] for any question, feedback or request.
|