Instructions to use flax-community/roberta-swahili with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/roberta-swahili with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/roberta-swahili")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-swahili") model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-swahili", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 461ac25b524bb55d4867f66b524231c3dfaddd179de203a70c8cfec6ac6946c0
- Size of remote file:
- 422 MB
- SHA256:
- 81d3951d9b61b4d8b8a57d880abd099fef5dbfdf913e9b523fe46fab1bf68ee0
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