Instructions to use jean-paul/KinyaBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jean-paul/KinyaBERT-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jean-paul/KinyaBERT-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jean-paul/KinyaBERT-small") model = AutoModelForMaskedLM.from_pretrained("jean-paul/KinyaBERT-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea00093f24e5cc626c29bd0ee78ad049f47826e9262bb10e3a03b090e20eaf7e
- Size of remote file:
- 266 MB
- SHA256:
- a563255e9930f9018c17eee9fa59762ae7a97541e43d439e5b14ca1f3aae10cc
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