Instructions to use hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering 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-MPNetForQuestionAnswering 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-MPNetForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MPNetForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bee94daf76e21548f965ab8e69f177bb3c4738d116fcd0099a20fc239cb18196
- Size of remote file:
- 1.06 MB
- SHA256:
- ceb636854ded6a772822b29e55295ea9c2e3d299c66c02821f3a708aab315b0f
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