Instructions to use hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering 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-RoFormerForQuestionAnswering 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-RoFormerForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-RoFormerForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c3da73f90510473d034fca1d5a08fd2d9872c7692f14e73851bfe8a411bb653
- Size of remote file:
- 6.56 MB
- SHA256:
- 926f59c2c0e21daad9ec5074e7bdf4dd17e7e762da58c989ba78f1cd334f6a4c
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