Instructions to use asafaya/albert-xlarge-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/albert-xlarge-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/albert-xlarge-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/albert-xlarge-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/albert-xlarge-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 485c916f6d9731e6da866d680cd7247d22a2a412854d6eafa69eec4a083424ba
- Size of remote file:
- 252 MB
- SHA256:
- 18e4a4d8cc6a8d506068b9c2f7f073eaa0e0f1777a19e99d83cd6e8bac234ad1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.