Instructions to use Chetna19/albert-base-v2_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chetna19/albert-base-v2_qa_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Chetna19/albert-base-v2_qa_model")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Chetna19/albert-base-v2_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Chetna19/albert-base-v2_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5aa276805f78d52175d57b8dceb758b2921b3a75a7ee59356bde507dfd04815
- Size of remote file:
- 44.4 MB
- SHA256:
- 35eb4b3c2f0271dffde56f9eaebf600d9a2b516eb20e9b4c719c4e9fd6a79219
路
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