Instructions to use hf-internal-testing/tiny-random-DebertaV2ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-DebertaV2ForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13e7a7300d5214b215ac238ce46cc389cd06193953fa22c1d20e7eef11860619
- Size of remote file:
- 16.6 MB
- SHA256:
- b662d7c4a13bd983a271e96e853a89397e7bd9b4f77cadc87b98d4ed0d4e1596
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