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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37fc8b74a8198ac9869f523bb990e45e34d24830093a71f2c814ff09b0a974d1
- Size of remote file:
- 820 Bytes
- SHA256:
- f3f5754bf6d9b3307df335ec10c3deb6991443693ea3b274344b7bd6723036b6
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