Instructions to use hf-tiny-model-private/tiny-random-LukeForQuestionAnswering 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-LukeForQuestionAnswering 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-LukeForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LukeForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-LukeForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bb666a744ee6a9582482bff753599d61f5266499a5eb60d7ac002e41c11a4b7
- Size of remote file:
- 6.78 MB
- SHA256:
- f820f44658493802da472b7d7cf39e12779959299b255d8b13c51c2388e6cfd2
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