Instructions to use hf-tiny-model-private/tiny-random-ElectraForQuestionAnswering 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-ElectraForQuestionAnswering 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-ElectraForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ElectraForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-ElectraForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37e6b0ed6e13a55c938c3df523849509f2b57b07deacc4b7f5f359a72316f717
- Size of remote file:
- 1.01 MB
- SHA256:
- ebec5ed4bf43b589ca35e4d3f72c4fcb1a1c7d2687fa106175659333fa8687e3
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