Instructions to use Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-Gemma3_PersianQuAD_QA-3epochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-Gemma3_PersianQuAD_QA-3epochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-Gemma3_PersianQuAD_QA-3epochs")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-Gemma3_PersianQuAD_QA-3epochs") model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD-finetuned-Gemma3_PersianQuAD_QA-3epochs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac777b0b3c6bf10b26a4a06dcd53bc4489e41ec5f0189cdba8f0ac05f5bed172
- Size of remote file:
- 5.97 kB
- SHA256:
- cfdafc6d31fd230c2b3706daa7ee5a8fc61144cb5a838306b8b59a683060d3d7
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