Instructions to use awwab-ahmed/bert-base-arabic-camelbert-mix-finetuned-AR-dotted-mediumPlus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awwab-ahmed/bert-base-arabic-camelbert-mix-finetuned-AR-dotted-mediumPlus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="awwab-ahmed/bert-base-arabic-camelbert-mix-finetuned-AR-dotted-mediumPlus")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("awwab-ahmed/bert-base-arabic-camelbert-mix-finetuned-AR-dotted-mediumPlus") model = AutoModelForMaskedLM.from_pretrained("awwab-ahmed/bert-base-arabic-camelbert-mix-finetuned-AR-dotted-mediumPlus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 957057f4c1ec8dfd1aa508326626fe107e47a3b99f7c0dba575cf34ac78b0d8f
- Size of remote file:
- 530 MB
- SHA256:
- 1096df562c51e70bbcd2c39d4f54276baee64a1171348dc3ceb8d0d72fa3a807
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