Instructions to use hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering 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-ConvBertForQuestionAnswering 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-ConvBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2664c4f40586428cb710367e54d7d99f8d8661ad59a4459705b0dd8aa6c8f194
- Size of remote file:
- 5.34 MB
- SHA256:
- b830f8aecd5dee782d21bf6177020762633447d0e4ec7371e6f6bf60731e1a38
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