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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16473ea5ea74d935659f0eb32b3cdbaa6c1b6beba96805f624bf6f1cbb4d32c3
- Size of remote file:
- 4.21 MB
- SHA256:
- 117974972f745b06b1ddbe0f839168671fc08bacc08e90ec2d43454ab196c02a
路
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