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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8eddcf0bb0ae3e0b7c9608db8d4df2b819764b758ddf5c47168521f77605be5
- Size of remote file:
- 442 kB
- SHA256:
- 6171a9f072f2f8a7fb5420b2c8480000e5912f1f106c6cdb94b3d8b4200bcf11
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