Instructions to use TransWiC/xlmr-large-ar-BT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-ar-BT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-ar-BT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-ar-BT") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-ar-BT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bc5d1463905af399e62a551f0cfa28bcfc5e965670678f24f70d4a2d39f2667
- Size of remote file:
- 2.26 GB
- SHA256:
- 2dfde0905c79493b4163797fd8b0bfb865667fd708270c7b0787739dcb1e7bdb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.