Instructions to use hf-tiny-model-private/tiny-random-DebertaV2ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DebertaV2ForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-DebertaV2ForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaV2ForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-DebertaV2ForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 609df1205be461ac958d12c6164333e39419a8940e312313bee382e5f2918cf5
- Size of remote file:
- 16.6 MB
- SHA256:
- 1416686d489e1e5b35a722d2e81c596de8604d4873e2e510ced5b959d8251e52
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