Instructions to use hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-XLNetForQuestionAnsweringSimple", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e953475efbcf368c2d1749d10235aebdf4155bc7ecfb1457e1adec139d909e5a
- Size of remote file:
- 4.4 MB
- SHA256:
- d5c437990c5ed32809556ef3fc7610e4ccf76f09fe7c2ac84e19d7a70c8bf573
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