Instructions to use Davlan/afro-xlmr-large-29L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-large-29L with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-large-29L")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-large-29L") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-large-29L", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 10e1b783f337e76c853a0fb6d37ad23309bb3838911f59a966f7295a94271b46
- Size of remote file:
- 2.24 GB
- SHA256:
- 4b1850db844bc186e3cf0e1898a275f41cdaf2fc10af5f7d5e1c8f4179d0c0b0
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