Instructions to use hf-tiny-model-private/tiny-random-MobileBertForQuestionAnswering 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-MobileBertForQuestionAnswering 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-MobileBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MobileBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46c95360929b5a27ef5f22fe09c271733d67db258cf4195847f39bff2b4a5089
- Size of remote file:
- 2.85 MB
- SHA256:
- 5afbec4f4ce25380f4ae48745f30183433286f255afad4f92040604b33318f60
路
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