Instructions to use hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecTextForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9e1a804e6077b76f95eb3f2093fb9b1ddd0883a4bfedcd069648fdeb5f9f45f
- Size of remote file:
- 349 kB
- SHA256:
- 2cd39beb1fa929bf7523e65e17a464aaaf4c2b0b1f24b77bf56812c441d5534a
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