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:
- 67f3abd65077a1994209dbfa34c92225e3268c24e579180461037dab4baac231
- Size of remote file:
- 368 kB
- SHA256:
- ec458a36b3c730aa95adfafb20fe81192ebbfc27eb7242eb27c4dc5ea06854d0
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