Instructions to use ArabicArgument/News_Claim_Arabic_BERT_Large_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArabicArgument/News_Claim_Arabic_BERT_Large_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ArabicArgument/News_Claim_Arabic_BERT_Large_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ArabicArgument/News_Claim_Arabic_BERT_Large_Model") model = AutoModelForSequenceClassification.from_pretrained("ArabicArgument/News_Claim_Arabic_BERT_Large_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ArabicArgument/News_Claim_Arabic_BERT_Large_Model: direct link, hf CLI and curl.
- Browser
- Download file 837 kB
-
https://huggingface.co/ArabicArgument/News_Claim_Arabic_BERT_Large_Model/resolve/main/tokenizer.json
- Command line
-
hf download hf://ArabicArgument/News_Claim_Arabic_BERT_Large_Model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ArabicArgument/News_Claim_Arabic_BERT_Large_Model/resolve/main/tokenizer.json
837 kB
File too large to display, you can check the raw version instead.