Instructions to use hf-internal-testing/tiny-random-UMT5ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-UMT5ForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-UMT5ForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-UMT5ForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-UMT5ForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68ed313ad1005190df2b193f58d95e0aad022ae821bf02581b8c2ed0cadb22b3
- Size of remote file:
- 33.2 MB
- SHA256:
- 959ea3d84f4cb58e414614d4fec624d108fb23e664278dabf86e354b14e00f4d
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