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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 802c932b094f4d8b54153d114db8fa2bea9d794459a1b078731bf074e03af68c
- Size of remote file:
- 1.79 MB
- SHA256:
- 1a3884b3841e3a759768e3286cf5b3fff6bfb995975b83513629e77398065107
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