Instructions to use hf-tiny-model-private/tiny-random-IBertForQuestionAnswering 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-IBertForQuestionAnswering 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-IBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-IBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-IBertForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4d4a498f5beef4c3e17b92bd8a85815c9cb34ddc8948b1a496fbbee1c636cae
- Size of remote file:
- 725 kB
- SHA256:
- 9306f770f3de795d23fd3c1b06ee5325d73d9ef757226b2307c3e5f94fc5d6a6
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