Instructions to use hf-internal-testing/tiny-random-MT5ForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MT5ForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-MT5ForQuestionAnswering", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MT5ForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-MT5ForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9093f6e016a2c6dd52e5c44be5bda0f3e64dcc084bb97b8242bcbb7deeb0a195
- Size of remote file:
- 32.2 MB
- SHA256:
- f7f3332429a2d2d2cfd95c137848c3e225bebdbe516d05b7e1a5236f61c9290f
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