Instructions to use ahmedJaafari/DarElectra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmedJaafari/DarElectra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ahmedJaafari/DarElectra")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ahmedJaafari/DarElectra") model = AutoModelForMaskedLM.from_pretrained("ahmedJaafari/DarElectra", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c08742f2699e08ca3cfddae26b05a36f655e74265577bea96052767ba230d473
- Size of remote file:
- 210 MB
- SHA256:
- 6070812dc5ae8f05d02d086ad4165cdfe113a3884c8846d7f0ec926d80c29032
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