Instructions to use Ahmade/questionAnswerv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmade/questionAnswerv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Ahmade/questionAnswerv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ahmade/questionAnswerv2") model = AutoModelForQuestionAnswering.from_pretrained("Ahmade/questionAnswerv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c12fc1e1ab2f0f3b7fab7b7a60f6f28dfbdad2d79df942dd5ba3b0b1aa052b0
- Size of remote file:
- 431 MB
- SHA256:
- 856a3c815589e96c8e6658daa794f8925bd3e571e23843fccac82b459669dd0d
路
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