Instructions to use MMars/Question_Answering_AraBERT_xtreme_ar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MMars/Question_Answering_AraBERT_xtreme_ar with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="MMars/Question_Answering_AraBERT_xtreme_ar")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("MMars/Question_Answering_AraBERT_xtreme_ar") model = AutoModelForQuestionAnswering.from_pretrained("MMars/Question_Answering_AraBERT_xtreme_ar", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:11c69415f1a5dcbec0a0626896497ec186ce02540ff221ecc8820fd1a7fcbf7f
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size 538444704
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