Instructions to use Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-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_DeepseekQA_WS_QA_embedding-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_DeepseekQA_WS_QA_embedding-3epochs")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs") model = AutoModelForQuestionAnswering.from_pretrained("Z-Jafari/bert-fa-base-uncased-finetuned-PersianQuAD_DeepseekQA_WS_QA_embedding-3epochs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d23abaf8bf994262bae86121bd436f4106a777891ce954871fe90f0f233daeeb
- Size of remote file:
- 649 MB
- SHA256:
- a238ede55a27400507a2935a14ca7b6c0980e76838e31f685965ed63b4997f2b
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