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:
- 7c624c7026653f559edd70ce54c6b655a83b8993fd9740c4b38b904b2d50678e
- Size of remote file:
- 6.81 MB
- SHA256:
- d3347389d69dbdd11cf39cf7937be6c27b2750b197718a164a7f434e548bc66a
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