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:
- e750bb82fbaa119706c74348dc5f0ebb4d15c34dd94c23d52ffbf533496ea524
- Size of remote file:
- 2.88 kB
- SHA256:
- a93f9d54e97a20901c05931159fd6564121e5ee6c1f41b84497e9685598102bd
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