Instructions to use Zaid/mbert_xquad_ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zaid/mbert_xquad_ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Zaid/mbert_xquad_ar")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Zaid/mbert_xquad_ar") model = AutoModelForQuestionAnswering.from_pretrained("Zaid/mbert_xquad_ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Zaid/mbert_xquad_ar: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Zaid/mbert_xquad_ar/resolve/main/training_args.bin
- Command line
-
hf download hf://Zaid/mbert_xquad_ar/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Zaid/mbert_xquad_ar/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 5c603f319777b1199e0e5324adfa55a928ca0c9950793379a2a06a542b2d0ecb
- Size of remote file:
- 3.52 kB
- SHA256:
- a182a990d8fe8f6d733064c162a859d012e5780fc2650c085e8e8aab6d0946b6
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.