Instructions to use hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering 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-RemBertForQuestionAnswering 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-RemBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-RemBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 053289873af73962ab5b5ef87010935886d19b6010ea2548bf34969836350728
- Size of remote file:
- 18.2 MB
- SHA256:
- 9507acc9739c0ab39d32b9ad33c4580ea921537338d16f7bbd39a24b212689f8
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