Instructions to use TransWiC/xlmr-large-en-CLS-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-en-CLS-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-en-CLS-P")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-en-CLS-P") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-en-CLS-P", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f9e7ec2fa9bc8fd7020c3b63634935db603c5d486629f46c292b678f19416ee
- Size of remote file:
- 2.28 GB
- SHA256:
- 33813b359e74eca63e71208ccc2ca4be77e8eff476e7935142bc08ac7f925c46
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