Instructions to use hf-internal-testing/tiny-random-NezhaForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-NezhaForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-NezhaForQuestionAnswering")# Load model directly from transformers import AutoModelForQuestionAnswering model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-NezhaForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4d45f8abec1950b3bd0b50420d40366eb91bc3d9b5837fe871f7005833f7d64
- Size of remote file:
- 2.91 MB
- SHA256:
- fca4adc5a4673e203e70cba603cb9845357c6e3e4a5558b43e2e4850eac2bca6
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