metadata
language: sw
widget:
- text: Si kila mwenye makucha <mask> simba.
datasets:
- flax-community/swahili-safi
RoBERTa in Swahili
This model was trained using HuggingFace's Flax framework and is part of the JAX/Flax Community Week organized by HuggingFace. All training was done on a TPUv3-8 VM sponsored by the Google Cloud team.
How to use
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-swahili")
model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-swahili")
print(round((model.num_parameters())/(1000*1000)),"Million Parameters")
105 Million Parameters
Training Data:
This model was trained on Swahili Safi
Results:
Eval metrics: {'f1': 86%}
This model was fine-tuned based off this model for the Zindi News Classification Challenge
More Details:
For more details and Demo please check HF Swahili Space