Instructions to use hf-internal-testing/tiny-random-XLMForQuestionAnsweringSimple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLMForQuestionAnsweringSimple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-XLMForQuestionAnsweringSimple")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLMForQuestionAnsweringSimple") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-XLMForQuestionAnsweringSimple") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15b3677d3c162d2d5b609a23c7ba38dd5adeb6faed4433ede4c9e3ca25833a27
- Size of remote file:
- 4.19 MB
- SHA256:
- 6210189882b1a06b78418252e53d7eb950f6576381f4c503d8d6063d6a8e8955
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