Instructions to use akhooli/ModernBERT-ar-base-14m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akhooli/ModernBERT-ar-base-14m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="akhooli/ModernBERT-ar-base-14m")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("akhooli/ModernBERT-ar-base-14m") model = AutoModelForMaskedLM.from_pretrained("akhooli/ModernBERT-ar-base-14m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from akhooli/ModernBERT-ar-base-14m: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/akhooli/ModernBERT-ar-base-14m/resolve/main/training_args.bin
- Command line
-
hf download hf://akhooli/ModernBERT-ar-base-14m/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/akhooli/ModernBERT-ar-base-14m/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 3c3326d9da4380505970f794dcac88d06475c07f60b09ef2548b95bfdf1337bd
- Size of remote file:
- 5.3 kB
- SHA256:
- 99870a7d7b34565ce690f933b6840e04e574a58f86e974df398af6b69bbe4a3f
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