Instructions to use Davlan/afro-xlmr-large-61L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-large-61L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-large-61L")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-large-61L") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-large-61L", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c36a3ba914b42a70220c05f962010fd86c71147f9427a0f4229dab356741c127
- Size of remote file:
- 2.24 GB
- SHA256:
- 05dddaef12a0cbd0799143e39bc860a4fd46c76c4854a3a66e7c6a0dca4aba91
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