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:
- 30ece10f0050d4b9f7c22c0accea4fc0ffb8725589e1caacb4633e21fcbcf3ab
- Size of remote file:
- 16.8 MB
- SHA256:
- fc7a6fe5180d0c75009dfa0995b9215bdd5a56f5a65e1dc6252eb89bdcafa920
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