Instructions to use hf-internal-testing/tiny-random-MraForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-MraForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-MraForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b03f23bbcc1a538f8d7c5dc8f0df9568b0631454edce3da696897c8de8a2aaf
- Size of remote file:
- 179 kB
- SHA256:
- c1bbf1c5411f6967fdf7a2c2386a890a9588389d4a1751dc39efe63e4e1683db
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