Instructions to use Rogendo/afribert-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rogendo/afribert-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Rogendo/afribert-mlm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Rogendo/afribert-mlm") model = AutoModelForMaskedLM.from_pretrained("Rogendo/afribert-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Rogendo/afribert-mlm: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/Rogendo/afribert-mlm/resolve/main/training_args.bin
- Command line
-
hf download hf://Rogendo/afribert-mlm/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Rogendo/afribert-mlm/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- 0e26275b6cb7cf284ca5400be9d955b7d5d762403ff79f8a0413012da6cddafe
- Size of remote file:
- 5.2 kB
- SHA256:
- 70e0c88a8df692a6196f27c41ff1dd6050248ad72f8a5d77df305ea22dfb6bde
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