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:
- 7916f671d381fd02a73d531ca2d66a989fa42488bbacfe5aac204bc271297c57
- Size of remote file:
- 138 kB
- SHA256:
- f586ddbfe9e09ec1b1f14b834fd111d1f57cf08ab7a370b30f7bfae7667da526
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