Instructions to use hf-internal-testing/tiny-random-Data2VecTextForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-Data2VecTextForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9e590da499d5249be3517df4ef8190fcf516ad8a497d18f8e2e5c85d99c1a38
- Size of remote file:
- 467 kB
- SHA256:
- cc147c36a02a35e4452d939839074f685a545e3a6a9e931c1fcfb3b729612613
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