Instructions to use dewdev/question_and_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dewdev/question_and_answer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="dewdev/question_and_answer")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("dewdev/question_and_answer") model = AutoModelForQuestionAnswering.from_pretrained("dewdev/question_and_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e65598c36dac9c3f44363c8eb6295c3c56720060bd062b13efe465951fa7074f
- Size of remote file:
- 261 MB
- SHA256:
- 39b1e16e852684d39469b025c60c1d4703b49726b9b93dfe3159dde4bd650287
路
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