Instructions to use betteib/bert-base-arabert-finetuned-mdeberta-tn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use betteib/bert-base-arabert-finetuned-mdeberta-tn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="betteib/bert-base-arabert-finetuned-mdeberta-tn")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("betteib/bert-base-arabert-finetuned-mdeberta-tn") model = AutoModelForMaskedLM.from_pretrained("betteib/bert-base-arabert-finetuned-mdeberta-tn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c132548845625c3a10783f42655d4d8f94c69d88378ee4aaaf2c79bbc3283f98
- Size of remote file:
- 4.98 kB
- SHA256:
- e4255bd6ff5e38c120d164217b0604c1ed377a9ced2d4d38b48122900b631d33
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