Instructions to use salti/xlm-roberta-large-arabic_qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use salti/xlm-roberta-large-arabic_qa with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="salti/xlm-roberta-large-arabic_qa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("salti/xlm-roberta-large-arabic_qa") model = AutoModelForQuestionAnswering.from_pretrained("salti/xlm-roberta-large-arabic_qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from salti/xlm-roberta-large-arabic_qa: direct link, hf CLI and curl.
- Browser
- Download file 1.47 kB
-
https://huggingface.co/salti/xlm-roberta-large-arabic_qa/resolve/main/training_args.bin
- Command line
-
hf download hf://salti/xlm-roberta-large-arabic_qa/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/salti/xlm-roberta-large-arabic_qa/resolve/main/training_args.bin
1.47 kB
- Xet hash:
- 8666d36f2702133c22efc09b2ce51f1ed91f5e1d8161bb4f9139303072fd7568
- Size of remote file:
- 1.47 kB
- SHA256:
- 43ca5c6f4fc5788e7a4c4273571d7eaf49887d3dc51260428a8f911add41c667
路
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