Instructions to use Davlan/afro-xlmr-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/afro-xlmr-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Davlan/afro-xlmr-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Davlan/afro-xlmr-large") model = AutoModelForMaskedLM.from_pretrained("Davlan/afro-xlmr-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Davlan/afro-xlmr-large: direct link, hf CLI and curl.
- Browser
- Download file 4.78 kB
-
https://huggingface.co/Davlan/afro-xlmr-large/resolve/main/training_args.bin
- Command line
-
hf download hf://Davlan/afro-xlmr-large/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Davlan/afro-xlmr-large/resolve/main/training_args.bin
4.78 kB
- Xet hash:
- 5745f84cf27046b78cd942e3c8ef92c211c5abcad584275e2197c42e8e8b7e97
- Size of remote file:
- 4.78 kB
- SHA256:
- 75b4c2eeacd6938b19bb16ff0ac287299cdcfe588eb3deeb056046c1ec66a3c6
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