Instructions to use Chetna19/bert_qa_model_electronics_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chetna19/bert_qa_model_electronics_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chetna19/bert_qa_model_electronics_1")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/bert_qa_model_electronics_1") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/bert_qa_model_electronics_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fc7ac23878a290185d245494a1396c27e72f3d8e3022371720a884642e21307
- Size of remote file:
- 3.58 kB
- SHA256:
- 836b003b9d95918bcbc1974d16faebab54bdb338d212003a532a8ec48b4a52cd
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