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:
- 7e3b10ad52aeca0338213fd0a263cab95e64f64fe1dd36db2b8e736842d46d8f
- Size of remote file:
- 3.11 MB
- SHA256:
- d79b8636f9723d276edc035935cd8b06c994e0d0ced868aa1f476ad497b8ed66
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