Instructions to use TransWiC/xlmr-large-all-CLS-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-all-CLS-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-all-CLS-P")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-all-CLS-P") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-all-CLS-P", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9dcaf2c44707479f2ca45c13d3c19d1119173155b670f9c9050fcf1dd0d5954
- Size of remote file:
- 2.88 kB
- SHA256:
- fd9fcb3939406d190d6cdc7031742f55bc17db7733ffb0ca7404a404b70ea902
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.