Instructions to use TransWiC/xlmr-large-ar-CLS-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-ar-CLS-B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-ar-CLS-B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-ar-CLS-B") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-ar-CLS-B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7a21159c814979db7d2f9a526a8faa1c664df952245776a30edb84cdec243f0
- Size of remote file:
- 4.55 GB
- SHA256:
- a73a4230f3e68dcc3e9751ba4943913848f29d32d69b7157fc26481848e9e3bd
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