|
--- |
|
language: sw |
|
widget: |
|
- text: "Si kila mwenye makucha [MASK] simba." |
|
datasets: |
|
- flax-community/swahili-safi |
|
--- |
|
|
|
## BERT base-uncased for in Swahili |
|
|
|
This model was trained using HuggingFace's Flax framework and is part of the [JAX/Flax Community Week](https://discuss.huggingface.co/t/open-to-the-community-community-week-using-jax-flax-for-nlp-cv/7104) organized by [HuggingFace](https://huggingface.co). All training was done on a TPUv3-8 VM sponsored by the Google Cloud team. |
|
|
|
## How to use |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForMaskedLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("flax-community/bert-base-uncased-swahili") |
|
|
|
model = AutoModelForMaskedLM.from_pretrained("flax-community/bert-base-uncased-swahili") |
|
|
|
print(round((model.num_parameters())/(1000*1000)),"Million Parameters") |
|
|
|
110 Million Parameters |
|
``` |
|
|
|
#### **Training Data**: |
|
This model was trained on [Swahili Safi](https://huggingface.co/datasets/flax-community/swahili-safi) |
|
|
|
|
|
#### **More Details**: |
|
For more details and Demo please check [HF Swahili Space](https://huggingface.co/spaces/flax-community/Swahili) |
|
|
