Instructions to use hf-tiny-model-private/tiny-random-BertForQuestionAnswering 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-BertForQuestionAnswering 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-BertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-BertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1304e95cca8ab6da3b159da84a71bc6c1117e6df9edb86f4a64b4661449baf73
- Size of remote file:
- 361 kB
- SHA256:
- f34670000ce57b7ca7439b7e809cd75f29358363c82d6d3902125e658bce3086
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