Instructions to use TransWiC/xlmr-large-ar-P with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TransWiC/xlmr-large-ar-P with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TransWiC/xlmr-large-ar-P")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TransWiC/xlmr-large-ar-P") model = AutoModelForSequenceClassification.from_pretrained("TransWiC/xlmr-large-ar-P", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from TransWiC/xlmr-large-ar-P: direct link, hf CLI and curl.
- Browser
- Download file 4.5 GB
-
https://huggingface.co/TransWiC/xlmr-large-ar-P/resolve/main/optimizer.pt
- Command line
-
hf download hf://TransWiC/xlmr-large-ar-P/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/TransWiC/xlmr-large-ar-P/resolve/main/optimizer.pt
4.5 GB
- Xet hash:
- 791d4116bc3a7c776644118157206ddf6fa81b275b294682349be758b66e711f
- Size of remote file:
- 4.5 GB
- SHA256:
- 936ce59694f91eb81abdcfeca3fffc674007e305072bcfcdc8d45578c3860e1f
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