Instructions to use hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering 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-AlbertForQuestionAnswering 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-AlbertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-AlbertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73fdce2fbf45fa2c7e1e81fdc5b9be0f98843362b863ce7d720414fac6712cdf
- Size of remote file:
- 16 MB
- SHA256:
- 103a9bf24fbe2738f7b928236276e76a1c5de7228f1c620ef336666d12c578de
路
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