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:
- 77e759f5204578f621466c980aa1f51c6f8fa25fb8c4f32efc9d71ce56715638
- Size of remote file:
- 32.2 MB
- SHA256:
- 657ad043ff244c92fc561f204abce829ff7b69d4497d7e9ad47b7cb5182a1a65
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