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:
- 3ae7eedb27e089fbe452bf62dbf8e82e3669be4b875133a4d28171b4ff4d153e
- Size of remote file:
- 4.46 MB
- SHA256:
- 076b43bab01118cb84ba8977c1b0533d14744354c78276823153183762d1404a
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