Instructions to use DigitalUmuganda/mbaza_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DigitalUmuganda/mbaza_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="DigitalUmuganda/mbaza_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("DigitalUmuganda/mbaza_bert") model = AutoModelForMaskedLM.from_pretrained("DigitalUmuganda/mbaza_bert") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- mbazaNLP/kinyarwanda_monolingual_v01.1
language:
- rw
pipeline_tag: fill-mask
library_name: transformers
tags:
- mbaza
- kinyarwanda
- bert
Mbaza Bert is a bert model trained on Kinyarwanda dataset