Instructions to use hf-internal-testing/tiny-random-LEDForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LEDForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-LEDForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LEDForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-LEDForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 859b8e091c08f3144dff5bdd67eda999afb4cecfef57965d9516b416645f8b12
- Size of remote file:
- 1.23 MB
- SHA256:
- 5381baf73712c0e4ef22b5673a0a286c1858205e6730fbe8b8c01baeada68b91
路
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