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:
- 5798da39350f1fbc87e9b82b460b55f39f9aa7d220bc63e5382b57f93b6de36e
- Size of remote file:
- 16.6 MB
- SHA256:
- 99f7b2338fd95b415c5bf95ddceac75d3fc43225892c5f00d7cad42b08fb582c
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