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:
- c5836cd0c9fc7fb56a4676111edad16e572e010c0f3bcf674d0cf207bfc29fb5
- Size of remote file:
- 2.28 GB
- SHA256:
- 294a937c1e13bdb907569b589875ee1e6656310cc47055e2b1fba2ca9c24334a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.