Instructions to use hf-tiny-model-private/tiny-random-MvpForQuestionAnswering 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-MvpForQuestionAnswering 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-MvpForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MvpForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MvpForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70f20bb6839bc81521ce71c3a4784debbc368042e29a40ca8a5eb27d159c5490
- Size of remote file:
- 119 kB
- SHA256:
- a509011e73772b4ac244fd925bf1c8260fcc687ceb3b31e3edac6d9e2b1b42e9
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