Instructions to use castorini/afriberta_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/afriberta_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="castorini/afriberta_large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("castorini/afriberta_large") model = AutoModelForMaskedLM.from_pretrained("castorini/afriberta_large", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md (#2)
- Update README.md (1594a591e2b53ffd77b4f5939fdb0439e91e964e) Co-authored-by: Mofetoluwa Adeyemi <Mofe@users.noreply.huggingface.co>231d924
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Add TF weights (#1)
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added citation
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updated model card
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