Instructions to use abdoelsayed/AraDPR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdoelsayed/AraDPR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="abdoelsayed/AraDPR")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("abdoelsayed/AraDPR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 482d9060192bb6a9fa85bbbd3f77b2cc2f8bcb1b42982cc5d4b729cf52a4837e
- Size of remote file:
- 658 Bytes
- SHA256:
- 71f7bb19c970924b979e6ab24af1050eb4545b42c1b10b9d439c21f5162462f0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.