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:
- ef079515f260e70697d077b2d026391f0fbd5ca770eaa919ba177d853c95e39c
- Size of remote file:
- 6.58 MB
- SHA256:
- a5fe4f415245c1ed95bf22e669d282501f7c47bb30f94b92367e76163200cfb1
路
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