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:
- 15f9438b88d08e1b5928638e13c06db9a881c94168056c2041021f12c18f4a3d
- Size of remote file:
- 4.28 MB
- SHA256:
- 6fabb306e4866104c0aee2a60f69eb39382a1f2b40173383f4fb77a06e16ed81
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