Instructions to use hf-internal-testing/tiny-random-RoCBertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-RoCBertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-RoCBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-RoCBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-RoCBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a87a0df5903a80266f689dfa854efae993946e9a3617278e1ce663d8a313debe
- Size of remote file:
- 2.96 MB
- SHA256:
- 7d0d215357d341e4d74551dcc73db6d64d6d501503b798fac8b99d8897764e23
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