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:
- 5cf188920a3a27c8185f94362b648623c2ae1e1cd9ae97e0064c9066a593053b
- Size of remote file:
- 2.24 GB
- SHA256:
- dab1df35ca96f74c6a0993b96e4c0d4783e18f27a63ad584a9403e28bcd12e2e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.