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:
- 6f752d215dcf1abb349de0deddf33f6d5fc2cff083dc84565b765ea8c08a85fb
- Size of remote file:
- 2.8 MB
- SHA256:
- 166a4cc8ffcdb1bfa7214237a55daef8479fa4bbe5bf89ae6d3c994a5841c6b5
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