Instructions to use SeyedAli/Persian-QA-Bert-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeyedAli/Persian-QA-Bert-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="SeyedAli/Persian-QA-Bert-V1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SeyedAli/Persian-QA-Bert-V1") model = AutoModelForQuestionAnswering.from_pretrained("SeyedAli/Persian-QA-Bert-V1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eb2f8d78eb3b5f3ded0e5239c13157cf7a82088dc8e08a470bee6d1bc7a13a2
- Size of remote file:
- 4.03 kB
- SHA256:
- d1099f2d1043b4a6ccb247edda1982d114b5f5a9779afd9ae5b26f25404942cc
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