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:
- 68ce2bb57627fac8ae747204c5973ca15b4c14ceed5d153cc12d3c91183cb87e
- Size of remote file:
- 33.2 MB
- SHA256:
- 9a68306fb93387043d05d893a0df9c780c478dc5f6550d7c16fc2511c3faef64
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