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:
- c714a90cc11f87f51b4b1a62a65dc9d762512a996fa9a4bdfac096b3c91c8ef6
- Size of remote file:
- 3.64 kB
- SHA256:
- da8a76dd64b0a2c8dab7681f10aa1b1dbc2eb552146f3bfdb24e9f3013f33fa0
路
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