Instructions to use MoNafea01/bert-eou-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MoNafea01/bert-eou-classifier with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("aubmindlab/bert-base-arabertv02") model = PeftModel.from_pretrained(base_model, "MoNafea01/bert-eou-classifier") - Transformers
How to use MoNafea01/bert-eou-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MoNafea01/bert-eou-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MoNafea01/bert-eou-classifier") model = AutoModelForSequenceClassification.from_pretrained("MoNafea01/bert-eou-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d01e07f3c8e77d153b4574aab6a082b4bc052d94c44fa3cdac9058eb73179e9
- Size of remote file:
- 270 MB
- SHA256:
- 3b0c3c252793354a2fa22406bf8e91a545eef7a2d16eeb538509b702db57532c
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