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:
- 7f8ee367b2e0b3a23fee51bc66a8fc089f078dbf2f4e081a747525c24cd4ca48
- Size of remote file:
- 5.06 kB
- SHA256:
- 6933811e62df8e5fd35e6c537d689d34ba74301345dc027697bae0fc5fc3789a
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