Instructions to use hf-tiny-model-private/tiny-random-DebertaForQuestionAnswering 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-DebertaForQuestionAnswering 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-DebertaForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-DebertaForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4813dc232869ba570a58c40e32afdee0d84ed43630c8b0273f4f80d28b5bb434
- Size of remote file:
- 347 kB
- SHA256:
- 74812ef77734db507d19549795c6cf31e4e2ca60fe9c7b3b80454fb05ed9e30f
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