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
- Xet hash:
- 13fbbaa6fe073097fbc0e96027ceaa844686c5125c1b437711a46b5f53677993
- Size of remote file:
- 14.2 kB
- SHA256:
- 8e53d896497904a687b635b3c29af8487b5b04c1fb0d3bd316d03d031003fbc3
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