Instructions to use hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-SqueezeBertForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9118583bf2a69f21ad5fb00bf7f56fcd72a0c7e991a71b66f42a6133e4fee43e
- Size of remote file:
- 347 kB
- SHA256:
- 2bffec9e52ac545d0872aec5be94637cb1f5a7c8dc2af27baec5f3c5aad87177
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