Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForQuestionAnswering 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-RobertaPreLayerNormForQuestionAnswering 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-RobertaPreLayerNormForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5e36789f753091beae00169329ba73b7dda88f2b8e2aee97906a6d57de24baaf
- Size of remote file:
- 462 kB
- SHA256:
- 3bfc5c9247b46c40fc893b34b24dc8540901123f4bb912df8819b900daaf224b
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