Instructions to use SMG0/Model5_arabertv2_large_T1_WOS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SMG0/Model5_arabertv2_large_T1_WOS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SMG0/Model5_arabertv2_large_T1_WOS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SMG0/Model5_arabertv2_large_T1_WOS") model = AutoModelForSequenceClassification.from_pretrained("SMG0/Model5_arabertv2_large_T1_WOS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f91a02f932d4d32052a801e71bf5741b03ad7cb6077fbd744d82f26c1d384c7
- Size of remote file:
- 3.96 kB
- SHA256:
- 6ed87fd6454730da5364d44a91d684936dc0aaab1ca3bb26a39bda404e9c4315
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