Instructions to use hf-internal-testing/tiny-random-FNetForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FNetForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-FNetForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FNetForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-FNetForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb2b30775dd156065295f8a78e15631da54bf2f59866ccfba0f9ef7ddcc9e136
- Size of remote file:
- 708 kB
- SHA256:
- 0f848afb4cb35389f15819aad6b9b4bb65d8b6cec9613b6145bea94b4a045ab6
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