Instructions to use vpr30/newspaper-qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vpr30/newspaper-qa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="vpr30/newspaper-qa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("vpr30/newspaper-qa") model = AutoModelForQuestionAnswering.from_pretrained("vpr30/newspaper-qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b24e5c212643fa4f15afa16cba2352091641981f94fe76867dff75eb7d873a12
- Size of remote file:
- 4.54 kB
- SHA256:
- 3ce22b684e152978fa01136c6da8c04437fa40a2f5a157d8048d07a2b08dda3f
路
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