Instructions to use mrm8488/AfricanBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/AfricanBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/AfricanBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/AfricanBERTa") model = AutoModelForMaskedLM.from_pretrained("mrm8488/AfricanBERTa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8645d1d744fc2c21dfcfc92944c2df085a130ac9934cca4d410f5227537532df
- Size of remote file:
- 334 MB
- SHA256:
- 99b918dc75f10a242cdc5edbe0130aff10dc2fa7a2ad2de4df4d097515a173c2
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