Instructions to use Davlan/afro-xlmr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-base") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c5c483dc8cc8d4f43c81169a3a632609288f47cbd92edd25e38a929b1e73a0b
- Size of remote file:
- 1.11 GB
- SHA256:
- ddb9160d1657b9f574e5064e344c3096de69ff17faded546eebc0b13d5e584ed
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